From e25483c9600049443e1e8f4813514b795a9da833 Mon Sep 17 00:00:00 2001
From: Serene Moussaoui <serene.moussaoui@mail.utoronto.ca>
Date: Tue, 21 Apr 2026 10:52:48 -0400
Subject: [PATCH 1/2] completed assignment 1

---
 02_activities/assignments/assignment_1.ipynb | 194 +++++++++++++++++--
 1 file changed, 177 insertions(+), 17 deletions(-)

diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index 1d25bbcb3..efcbef428 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -96,7 +96,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here"
+    "wine_df.shape[0]\n",
+    "# 178"
    ]
   },
   {
@@ -114,7 +115,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here"
+    "wine_df.shape[1]\n",
+    "# 14"
    ]
   },
   {
@@ -132,7 +134,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here"
+    "wine_df['class'].dtype\n",
+    "# integer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0b5a193",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wine_df['class'].unique()\n",
+    "# 0, 1 and 2"
    ]
   },
   {
@@ -151,7 +165,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here"
+    "wine_df.shape[1] - 1\n",
+    "# 13"
    ]
   },
   {
@@ -204,7 +219,7 @@
    "id": "403ef0bb",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "It is important to standardize the predictor variables because KNN is distance based. Variables with larger scales will dominate the distance calculation and so standardization ensures that alll the variables contribute equally."
    ]
   },
   {
@@ -220,7 +235,7 @@
    "id": "fdee5a15",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "The response variable Class is not numerical. It is categorical despite .dtype outputting integer (likely because the Class values are numbers referring to a particular category). Therefore we cannot compute distance calculations (meaningfully) and so scaling is not needed."
    ]
   },
   {
@@ -236,7 +251,17 @@
    "id": "f0676c21",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Setting a seed ensures reproducibility when someone else runs my code. The specific value doesn't matter so long as it is fixed. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0c6cc557",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "np.random.seed(123) # I did not run this line since a seed will be set in the next few cells, but I included it here because it said to \"do so below\"."
    ]
   },
   {
@@ -249,6 +274,30 @@
     "Extend the code to create a non-overlapping test set for the predictors and response variables."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "654c31d6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a copy of the original 'wine_df' dataframe to ensure we're not modifying the original data\n",
+    "wine_scaled = predictors_standardized.copy()\n",
+    "wine_scaled[\"class\"] = wine_df[\"class\"] # need to add this column since predictors_standardized doesn't include class\n",
+    "wine_scaled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "836f930c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(wine_scaled.describe())\n",
+    "# all the predictors seem to be on comparable scales."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -260,8 +309,19 @@
     "np.random.seed(123)\n",
     "\n",
     "# split the data into a training and testing set. hint: use train_test_split !\n",
+    "wine_train, wine_test = train_test_split(\n",
+    "    wine_scaled,\n",
+    "    train_size=0.75,\n",
+    "    shuffle=True,\n",
+    "    stratify=wine_scaled[\"class\"]\n",
+    ")\n",
     "\n",
-    "# Your code here ..."
+    "# create predictor and response training and test sets:\n",
+    "X_train = wine_train.drop(\"class\", axis=1)\n",
+    "y_train = wine_train[\"class\"]\n",
+    "\n",
+    "X_test = wine_test.drop(\"class\", axis=1)\n",
+    "y_test = wine_test[\"class\"]\n"
    ]
   },
   {
@@ -289,7 +349,61 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here..."
+    "# 1. Initialize the KNN classifier\n",
+    "knn = KNeighborsClassifier()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45dfedef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 2. Define a parameter grid for n_neighbors ranging from 1 to 50\n",
+    "parameter_grid = {\n",
+    "    \"n_neighbors\": range(1, 51),\n",
+    "}\n",
+    "\n",
+    "parameter_grid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "94bd9d0f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 3. Implement a grid search using GridSearchCV with 10 fold cross validation to find the optimal number of neighbors\n",
+    "grid_search = GridSearchCV(\n",
+    "    estimator=knn,\n",
+    "    param_grid=parameter_grid,\n",
+    "    cv=10\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4bb32f37",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 4.1 Fit model on training data.\n",
+    "grid_search.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "721f7423",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 4.2 Return the best n_neighbours\n",
+    "grid_search.best_params_\n",
+    "# the best n_neighbours is 7"
    ]
   },
   {
@@ -310,7 +424,58 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here..."
+    "# assign the best k from grid search to a variable\n",
+    "best_k = grid_search.best_params_[\"n_neighbors\"]\n",
+    "best_k"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f958b9e6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# initialize a new KNN model using best k\n",
+    "knn_final = KNeighborsClassifier(n_neighbors=best_k)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6ea7d9b2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# fit the model on training data\n",
+    "knn_final.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fdb01d9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make predictions on the test set\n",
+    "y_pred = knn_final.predict(X_test)\n",
+    "\n",
+    "# add these predictions to the wine_test data set as a new column predicted_class\n",
+    "wine_test[\"predicted_class\"] = y_pred\n",
+    "wine_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2de5a14b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# evaluate accuracy_score\n",
+    "accuracy_score(y_test, y_pred)\n",
+    "# score is 0.933"
    ]
   },
   {
@@ -365,7 +530,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.4",
+   "display_name": "lcr-env",
    "language": "python",
    "name": "python3"
   },
@@ -379,12 +544,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "497a84dc8fec8cf8d24e7e87b6d954c9a18a327edc66feb9b9ea7e9e72cc5c7e"
-   }
+   "version": "3.11.14"
   }
  },
  "nbformat": 4,

From 034de0c6a96945cacc7bb66ef97a3fa3b8c34881 Mon Sep 17 00:00:00 2001
From: Serene Moussaoui <serene.moussaoui@mail.utoronto.ca>
Date: Tue, 21 Apr 2026 10:55:20 -0400
Subject: [PATCH 2/2] adjustment to completed assignment 1

---
 02_activities/assignments/assignment_1.ipynb | 3656 +++++++++++++++++-
 1 file changed, 3619 insertions(+), 37 deletions(-)

diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index efcbef428..8b11ea64d 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "4a3485d6-ba58-4660-a983-5680821c5719",
    "metadata": {},
    "outputs": [],
@@ -56,10 +56,288 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "a431d282-f9ca-4d5d-8912-71ffc9d8ea19",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>14.23</td>\n",
+       "      <td>1.71</td>\n",
+       "      <td>2.43</td>\n",
+       "      <td>15.6</td>\n",
+       "      <td>127.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.06</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>2.29</td>\n",
+       "      <td>5.64</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>3.92</td>\n",
+       "      <td>1065.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13.20</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>2.14</td>\n",
+       "      <td>11.2</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>2.65</td>\n",
+       "      <td>2.76</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>1.28</td>\n",
+       "      <td>4.38</td>\n",
+       "      <td>1.05</td>\n",
+       "      <td>3.40</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13.16</td>\n",
+       "      <td>2.36</td>\n",
+       "      <td>2.67</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.24</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>2.81</td>\n",
+       "      <td>5.68</td>\n",
+       "      <td>1.03</td>\n",
+       "      <td>3.17</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>14.37</td>\n",
+       "      <td>1.95</td>\n",
+       "      <td>2.50</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>3.85</td>\n",
+       "      <td>3.49</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>7.80</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>1480.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13.24</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.87</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>118.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>2.69</td>\n",
+       "      <td>0.39</td>\n",
+       "      <td>1.82</td>\n",
+       "      <td>4.32</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>2.93</td>\n",
+       "      <td>735.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>173</th>\n",
+       "      <td>13.71</td>\n",
+       "      <td>5.65</td>\n",
+       "      <td>2.45</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>1.68</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>7.70</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>1.74</td>\n",
+       "      <td>740.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>174</th>\n",
+       "      <td>13.40</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>2.48</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.41</td>\n",
+       "      <td>7.30</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>750.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>13.27</td>\n",
+       "      <td>4.28</td>\n",
+       "      <td>2.26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.59</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>10.20</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>176</th>\n",
+       "      <td>13.17</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.37</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>1.46</td>\n",
+       "      <td>9.30</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>1.62</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>14.13</td>\n",
+       "      <td>4.10</td>\n",
+       "      <td>2.74</td>\n",
+       "      <td>24.5</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>2.05</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>9.20</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>178 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     alcohol  malic_acid   ash  alcalinity_of_ash  magnesium  total_phenols  \\\n",
+       "0      14.23        1.71  2.43               15.6      127.0           2.80   \n",
+       "1      13.20        1.78  2.14               11.2      100.0           2.65   \n",
+       "2      13.16        2.36  2.67               18.6      101.0           2.80   \n",
+       "3      14.37        1.95  2.50               16.8      113.0           3.85   \n",
+       "4      13.24        2.59  2.87               21.0      118.0           2.80   \n",
+       "..       ...         ...   ...                ...        ...            ...   \n",
+       "173    13.71        5.65  2.45               20.5       95.0           1.68   \n",
+       "174    13.40        3.91  2.48               23.0      102.0           1.80   \n",
+       "175    13.27        4.28  2.26               20.0      120.0           1.59   \n",
+       "176    13.17        2.59  2.37               20.0      120.0           1.65   \n",
+       "177    14.13        4.10  2.74               24.5       96.0           2.05   \n",
+       "\n",
+       "     flavanoids  nonflavanoid_phenols  proanthocyanins  color_intensity   hue  \\\n",
+       "0          3.06                  0.28             2.29             5.64  1.04   \n",
+       "1          2.76                  0.26             1.28             4.38  1.05   \n",
+       "2          3.24                  0.30             2.81             5.68  1.03   \n",
+       "3          3.49                  0.24             2.18             7.80  0.86   \n",
+       "4          2.69                  0.39             1.82             4.32  1.04   \n",
+       "..          ...                   ...              ...              ...   ...   \n",
+       "173        0.61                  0.52             1.06             7.70  0.64   \n",
+       "174        0.75                  0.43             1.41             7.30  0.70   \n",
+       "175        0.69                  0.43             1.35            10.20  0.59   \n",
+       "176        0.68                  0.53             1.46             9.30  0.60   \n",
+       "177        0.76                  0.56             1.35             9.20  0.61   \n",
+       "\n",
+       "     od280/od315_of_diluted_wines  proline  class  \n",
+       "0                            3.92   1065.0      0  \n",
+       "1                            3.40   1050.0      0  \n",
+       "2                            3.17   1185.0      0  \n",
+       "3                            3.45   1480.0      0  \n",
+       "4                            2.93    735.0      0  \n",
+       "..                            ...      ...    ...  \n",
+       "173                          1.74    740.0      2  \n",
+       "174                          1.56    750.0      2  \n",
+       "175                          1.56    835.0      2  \n",
+       "176                          1.62    840.0      2  \n",
+       "177                          1.60    560.0      2  \n",
+       "\n",
+       "[178 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from sklearn.datasets import load_wine\n",
     "\n",
@@ -91,10 +369,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "56916892",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "178"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "wine_df.shape[0]\n",
     "# 178"
@@ -110,10 +399,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "df0ef103",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "wine_df.shape[1]\n",
     "# 14"
@@ -129,10 +429,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "47989426",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('int64')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "wine_df['class'].dtype\n",
     "# integer"
@@ -140,10 +451,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "f0b5a193",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 1, 2])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "wine_df['class'].unique()\n",
     "# 0, 1 and 2"
@@ -160,10 +482,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "bd7b0910",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "13"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "wine_df.shape[1] - 1\n",
     "# 13"
@@ -190,10 +523,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "cc899b59",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+      "0  1.518613   -0.562250  0.232053          -1.169593   1.913905   \n",
+      "1  0.246290   -0.499413 -0.827996          -2.490847   0.018145   \n",
+      "2  0.196879    0.021231  1.109334          -0.268738   0.088358   \n",
+      "3  1.691550   -0.346811  0.487926          -0.809251   0.930918   \n",
+      "4  0.295700    0.227694  1.840403           0.451946   1.281985   \n",
+      "\n",
+      "   total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+      "0       0.808997    1.034819             -0.659563         1.224884   \n",
+      "1       0.568648    0.733629             -0.820719        -0.544721   \n",
+      "2       0.808997    1.215533             -0.498407         2.135968   \n",
+      "3       2.491446    1.466525             -0.981875         1.032155   \n",
+      "4       0.808997    0.663351              0.226796         0.401404   \n",
+      "\n",
+      "   color_intensity       hue  od280/od315_of_diluted_wines   proline  \n",
+      "0         0.251717  0.362177                      1.847920  1.013009  \n",
+      "1        -0.293321  0.406051                      1.113449  0.965242  \n",
+      "2         0.269020  0.318304                      0.788587  1.395148  \n",
+      "3         1.186068 -0.427544                      1.184071  2.334574  \n",
+      "4        -0.319276  0.362177                      0.449601 -0.037874  \n"
+     ]
+    }
+   ],
    "source": [
     "# Select predictors (excluding the last column)\n",
     "predictors = wine_df.iloc[:, :-1]\n",
@@ -276,10 +636,288 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "654c31d6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.518613</td>\n",
+       "      <td>-0.562250</td>\n",
+       "      <td>0.232053</td>\n",
+       "      <td>-1.169593</td>\n",
+       "      <td>1.913905</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.034819</td>\n",
+       "      <td>-0.659563</td>\n",
+       "      <td>1.224884</td>\n",
+       "      <td>0.251717</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>1.847920</td>\n",
+       "      <td>1.013009</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.246290</td>\n",
+       "      <td>-0.499413</td>\n",
+       "      <td>-0.827996</td>\n",
+       "      <td>-2.490847</td>\n",
+       "      <td>0.018145</td>\n",
+       "      <td>0.568648</td>\n",
+       "      <td>0.733629</td>\n",
+       "      <td>-0.820719</td>\n",
+       "      <td>-0.544721</td>\n",
+       "      <td>-0.293321</td>\n",
+       "      <td>0.406051</td>\n",
+       "      <td>1.113449</td>\n",
+       "      <td>0.965242</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.196879</td>\n",
+       "      <td>0.021231</td>\n",
+       "      <td>1.109334</td>\n",
+       "      <td>-0.268738</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.215533</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>2.135968</td>\n",
+       "      <td>0.269020</td>\n",
+       "      <td>0.318304</td>\n",
+       "      <td>0.788587</td>\n",
+       "      <td>1.395148</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.691550</td>\n",
+       "      <td>-0.346811</td>\n",
+       "      <td>0.487926</td>\n",
+       "      <td>-0.809251</td>\n",
+       "      <td>0.930918</td>\n",
+       "      <td>2.491446</td>\n",
+       "      <td>1.466525</td>\n",
+       "      <td>-0.981875</td>\n",
+       "      <td>1.032155</td>\n",
+       "      <td>1.186068</td>\n",
+       "      <td>-0.427544</td>\n",
+       "      <td>1.184071</td>\n",
+       "      <td>2.334574</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.295700</td>\n",
+       "      <td>0.227694</td>\n",
+       "      <td>1.840403</td>\n",
+       "      <td>0.451946</td>\n",
+       "      <td>1.281985</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>0.663351</td>\n",
+       "      <td>0.226796</td>\n",
+       "      <td>0.401404</td>\n",
+       "      <td>-0.319276</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>0.449601</td>\n",
+       "      <td>-0.037874</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>173</th>\n",
+       "      <td>0.876275</td>\n",
+       "      <td>2.974543</td>\n",
+       "      <td>0.305159</td>\n",
+       "      <td>0.301803</td>\n",
+       "      <td>-0.332922</td>\n",
+       "      <td>-0.985614</td>\n",
+       "      <td>-1.424900</td>\n",
+       "      <td>1.274310</td>\n",
+       "      <td>-0.930179</td>\n",
+       "      <td>1.142811</td>\n",
+       "      <td>-1.392758</td>\n",
+       "      <td>-1.231206</td>\n",
+       "      <td>-0.021952</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>174</th>\n",
+       "      <td>0.493343</td>\n",
+       "      <td>1.412609</td>\n",
+       "      <td>0.414820</td>\n",
+       "      <td>1.052516</td>\n",
+       "      <td>0.158572</td>\n",
+       "      <td>-0.793334</td>\n",
+       "      <td>-1.284344</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.316950</td>\n",
+       "      <td>0.969783</td>\n",
+       "      <td>-1.129518</td>\n",
+       "      <td>-1.485445</td>\n",
+       "      <td>0.009893</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>0.332758</td>\n",
+       "      <td>1.744744</td>\n",
+       "      <td>-0.389355</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.422412</td>\n",
+       "      <td>-1.129824</td>\n",
+       "      <td>-1.344582</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>2.224236</td>\n",
+       "      <td>-1.612125</td>\n",
+       "      <td>-1.485445</td>\n",
+       "      <td>0.280575</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>176</th>\n",
+       "      <td>0.209232</td>\n",
+       "      <td>0.227694</td>\n",
+       "      <td>0.012732</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.422412</td>\n",
+       "      <td>-1.033684</td>\n",
+       "      <td>-1.354622</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>-0.229346</td>\n",
+       "      <td>1.834923</td>\n",
+       "      <td>-1.568252</td>\n",
+       "      <td>-1.400699</td>\n",
+       "      <td>0.296498</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>1.395086</td>\n",
+       "      <td>1.583165</td>\n",
+       "      <td>1.365208</td>\n",
+       "      <td>1.502943</td>\n",
+       "      <td>-0.262708</td>\n",
+       "      <td>-0.392751</td>\n",
+       "      <td>-1.274305</td>\n",
+       "      <td>1.596623</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>1.791666</td>\n",
+       "      <td>-1.524378</td>\n",
+       "      <td>-1.428948</td>\n",
+       "      <td>-0.595160</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>178 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+       "0    1.518613   -0.562250  0.232053          -1.169593   1.913905   \n",
+       "1    0.246290   -0.499413 -0.827996          -2.490847   0.018145   \n",
+       "2    0.196879    0.021231  1.109334          -0.268738   0.088358   \n",
+       "3    1.691550   -0.346811  0.487926          -0.809251   0.930918   \n",
+       "4    0.295700    0.227694  1.840403           0.451946   1.281985   \n",
+       "..        ...         ...       ...                ...        ...   \n",
+       "173  0.876275    2.974543  0.305159           0.301803  -0.332922   \n",
+       "174  0.493343    1.412609  0.414820           1.052516   0.158572   \n",
+       "175  0.332758    1.744744 -0.389355           0.151661   1.422412   \n",
+       "176  0.209232    0.227694  0.012732           0.151661   1.422412   \n",
+       "177  1.395086    1.583165  1.365208           1.502943  -0.262708   \n",
+       "\n",
+       "     total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+       "0         0.808997    1.034819             -0.659563         1.224884   \n",
+       "1         0.568648    0.733629             -0.820719        -0.544721   \n",
+       "2         0.808997    1.215533             -0.498407         2.135968   \n",
+       "3         2.491446    1.466525             -0.981875         1.032155   \n",
+       "4         0.808997    0.663351              0.226796         0.401404   \n",
+       "..             ...         ...                   ...              ...   \n",
+       "173      -0.985614   -1.424900              1.274310        -0.930179   \n",
+       "174      -0.793334   -1.284344              0.549108        -0.316950   \n",
+       "175      -1.129824   -1.344582              0.549108        -0.422075   \n",
+       "176      -1.033684   -1.354622              1.354888        -0.229346   \n",
+       "177      -0.392751   -1.274305              1.596623        -0.422075   \n",
+       "\n",
+       "     color_intensity       hue  od280/od315_of_diluted_wines   proline  class  \n",
+       "0           0.251717  0.362177                      1.847920  1.013009      0  \n",
+       "1          -0.293321  0.406051                      1.113449  0.965242      0  \n",
+       "2           0.269020  0.318304                      0.788587  1.395148      0  \n",
+       "3           1.186068 -0.427544                      1.184071  2.334574      0  \n",
+       "4          -0.319276  0.362177                      0.449601 -0.037874      0  \n",
+       "..               ...       ...                           ...       ...    ...  \n",
+       "173         1.142811 -1.392758                     -1.231206 -0.021952      2  \n",
+       "174         0.969783 -1.129518                     -1.485445  0.009893      2  \n",
+       "175         2.224236 -1.612125                     -1.485445  0.280575      2  \n",
+       "176         1.834923 -1.568252                     -1.400699  0.296498      2  \n",
+       "177         1.791666 -1.524378                     -1.428948 -0.595160      2  \n",
+       "\n",
+       "[178 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Create a copy of the original 'wine_df' dataframe to ensure we're not modifying the original data\n",
     "wine_scaled = predictors_standardized.copy()\n",
@@ -289,10 +927,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "836f930c",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "            alcohol    malic_acid           ash  alcalinity_of_ash  \\\n",
+      "count  1.780000e+02  1.780000e+02  1.780000e+02       1.780000e+02   \n",
+      "mean  -8.382808e-16 -1.197544e-16 -8.370333e-16      -3.991813e-17   \n",
+      "std    1.002821e+00  1.002821e+00  1.002821e+00       1.002821e+00   \n",
+      "min   -2.434235e+00 -1.432983e+00 -3.679162e+00      -2.671018e+00   \n",
+      "25%   -7.882448e-01 -6.587486e-01 -5.721225e-01      -6.891372e-01   \n",
+      "50%    6.099988e-02 -4.231120e-01 -2.382132e-02       1.518295e-03   \n",
+      "75%    8.361286e-01  6.697929e-01  6.981085e-01       6.020883e-01   \n",
+      "max    2.259772e+00  3.109192e+00  3.156325e+00       3.154511e+00   \n",
+      "\n",
+      "          magnesium  total_phenols    flavanoids  nonflavanoid_phenols  \\\n",
+      "count  1.780000e+02     178.000000  1.780000e+02          1.780000e+02   \n",
+      "mean  -3.991813e-17       0.000000 -3.991813e-16          3.592632e-16   \n",
+      "std    1.002821e+00       1.002821  1.002821e+00          1.002821e+00   \n",
+      "min   -2.088255e+00      -2.107246 -1.695971e+00         -1.868234e+00   \n",
+      "25%   -8.244151e-01      -0.885468 -8.275393e-01         -7.401412e-01   \n",
+      "50%   -1.222817e-01       0.095960  1.061497e-01         -1.760948e-01   \n",
+      "75%    5.096384e-01       0.808997  8.490851e-01          6.095413e-01   \n",
+      "max    4.371372e+00       2.539515  3.062832e+00          2.402403e+00   \n",
+      "\n",
+      "       proanthocyanins  color_intensity           hue  \\\n",
+      "count     1.780000e+02     1.780000e+02  1.780000e+02   \n",
+      "mean     -1.197544e-16     2.494883e-17  1.995907e-16   \n",
+      "std       1.002821e+00     1.002821e+00  1.002821e+00   \n",
+      "min      -2.069034e+00    -1.634288e+00 -2.094732e+00   \n",
+      "25%      -5.972835e-01    -7.951025e-01 -7.675624e-01   \n",
+      "50%      -6.289785e-02    -1.592246e-01  3.312687e-02   \n",
+      "75%       6.291754e-01     4.939560e-01  7.131644e-01   \n",
+      "max       3.485073e+00     3.435432e+00  3.301694e+00   \n",
+      "\n",
+      "       od280/od315_of_diluted_wines       proline       class  \n",
+      "count                  1.780000e+02  1.780000e+02  178.000000  \n",
+      "mean                   3.193450e-16 -1.596725e-16    0.938202  \n",
+      "std                    1.002821e+00  1.002821e+00    0.775035  \n",
+      "min                   -1.895054e+00 -1.493188e+00    0.000000  \n",
+      "25%                   -9.522483e-01 -7.846378e-01    0.000000  \n",
+      "50%                    2.377348e-01 -2.337204e-01    1.000000  \n",
+      "75%                    7.885875e-01  7.582494e-01    2.000000  \n",
+      "max                    1.960915e+00  2.971473e+00    2.000000  \n"
+     ]
+    }
+   ],
    "source": [
     "print(wine_scaled.describe())\n",
     "# all the predictors seem to be on comparable scales."
@@ -300,7 +984,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "72c101f2",
    "metadata": {},
    "outputs": [],
@@ -344,7 +1028,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "08818c64",
    "metadata": {},
    "outputs": [],
@@ -355,10 +1039,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "45dfedef",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'n_neighbors': range(1, 51)}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 2. Define a parameter grid for n_neighbors ranging from 1 to 50\n",
     "parameter_grid = {\n",
@@ -370,7 +1065,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "94bd9d0f",
    "metadata": {},
    "outputs": [],
@@ -385,10 +1080,999 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "4bb32f37",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1.light {\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: black;\n",
+       "  --sklearn-color-background: white;\n",
+       "  --sklearn-color-border-box: black;\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1.dark {\n",
+       "  --sklearn-color-text-on-default-background: white;\n",
+       "  --sklearn-color-background: #111;\n",
+       "  --sklearn-color-border-box: white;\n",
+       "  --sklearn-color-icon: #878787;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: center;\n",
+       "  justify-content: center;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-3) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-0);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-0);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table {\n",
+       "    font-family: monospace;\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary::marker {\n",
+       "    font-size: 0.7rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "    margin-top: 0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       "/*\n",
+       "    `table td`is set in notebook with right text-align.\n",
+       "    We need to overwrite it.\n",
+       "*/\n",
+       ".estimator-table table td.param {\n",
+       "    text-align: left;\n",
+       "    position: relative;\n",
+       "    padding: 0;\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left !important;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    background-color: transparent;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left !important;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       "/*\n",
+       "    Styles for parameter documentation links\n",
+       "    We need styling for visited so jupyter doesn't overwrite it\n",
+       "*/\n",
+       "a.param-doc-link,\n",
+       "a.param-doc-link:link,\n",
+       "a.param-doc-link:visited {\n",
+       "    text-decoration: underline dashed;\n",
+       "    text-underline-offset: .3em;\n",
+       "    color: inherit;\n",
+       "    display: block;\n",
+       "    padding: .5em;\n",
+       "}\n",
+       "\n",
+       "/* \"hack\" to make the entire area of the cell containing the link clickable */\n",
+       "a.param-doc-link::before {\n",
+       "    position: absolute;\n",
+       "    content: \"\";\n",
+       "    inset: 0;\n",
+       "}\n",
+       "\n",
+       ".param-doc-description {\n",
+       "    display: none;\n",
+       "    position: absolute;\n",
+       "    z-index: 9999;\n",
+       "    left: 0;\n",
+       "    padding: .5ex;\n",
+       "    margin-left: 1.5em;\n",
+       "    color: var(--sklearn-color-text);\n",
+       "    box-shadow: .3em .3em .4em #999;\n",
+       "    width: max-content;\n",
+       "    text-align: left;\n",
+       "    max-height: 10em;\n",
+       "    overflow-y: auto;\n",
+       "\n",
+       "    /* unfitted */\n",
+       "    background: var(--sklearn-color-unfitted-level-0);\n",
+       "    border: thin solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       "/* Fitted state for parameter tooltips */\n",
+       ".fitted .param-doc-description {\n",
+       "    /* fitted */\n",
+       "    background: var(--sklearn-color-fitted-level-0);\n",
+       "    border: thin solid var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".param-doc-link:hover .param-doc-description {\n",
+       "    display: block;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=10, estimator=KNeighborsClassifier(),\n",
+       "             param_grid={&#x27;n_neighbors&#x27;: range(1, 51)})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>GridSearchCV</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('estimator',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=estimator,-estimator%20object\">\n",
+       "            estimator\n",
+       "            <span class=\"param-doc-description\">estimator: estimator object<br><br>This is assumed to implement the scikit-learn estimator interface.<br>Either estimator needs to provide a ``score`` function,<br>or ``scoring`` must be passed.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">KNeighborsClassifier()</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('param_grid',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=param_grid,-dict%20or%20list%20of%20dictionaries\">\n",
+       "            param_grid\n",
+       "            <span class=\"param-doc-description\">param_grid: dict or list of dictionaries<br><br>Dictionary with parameters names (`str`) as keys and lists of<br>parameter settings to try as values, or a list of such<br>dictionaries, in which case the grids spanned by each dictionary<br>in the list are explored. This enables searching over any sequence<br>of parameter settings.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">{&#x27;n_neighbors&#x27;: range(1, 51)}</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scoring',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=scoring,-str%2C%20callable%2C%20list%2C%20tuple%20or%20dict%2C%20default%3DNone\">\n",
+       "            scoring\n",
+       "            <span class=\"param-doc-description\">scoring: str, callable, list, tuple or dict, default=None<br><br>Strategy to evaluate the performance of the cross-validated model on<br>the test set.<br><br>If `scoring` represents a single score, one can use:<br><br>- a single string (see :ref:`scoring_string_names`);<br>- a callable (see :ref:`scoring_callable`) that returns a single value;<br>- `None`, the `estimator`'s<br>  :ref:`default evaluation criterion <scoring_api_overview>` is used.<br><br>If `scoring` represents multiple scores, one can use:<br><br>- a list or tuple of unique strings;<br>- a callable returning a dictionary where the keys are the metric<br>  names and the values are the metric scores;<br>- a dictionary with metric names as keys and callables as values.<br><br>See :ref:`multimetric_grid_search` for an example.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=n_jobs,-int%2C%20default%3DNone\">\n",
+       "            n_jobs\n",
+       "            <span class=\"param-doc-description\">n_jobs: int, default=None<br><br>Number of jobs to run in parallel.<br>``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.<br>``-1`` means using all processors. See :term:`Glossary <n_jobs>`<br>for more details.<br><br>.. versionchanged:: v0.20<br>   `n_jobs` default changed from 1 to None</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('refit',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=refit,-bool%2C%20str%2C%20or%20callable%2C%20default%3DTrue\">\n",
+       "            refit\n",
+       "            <span class=\"param-doc-description\">refit: bool, str, or callable, default=True<br><br>Refit an estimator using the best found parameters on the whole<br>dataset.<br><br>For multiple metric evaluation, this needs to be a `str` denoting the<br>scorer that would be used to find the best parameters for refitting<br>the estimator at the end.<br><br>Where there are considerations other than maximum score in<br>choosing a best estimator, ``refit`` can be set to a function which<br>returns the selected ``best_index_`` given ``cv_results_``. In that<br>case, the ``best_estimator_`` and ``best_params_`` will be set<br>according to the returned ``best_index_`` while the ``best_score_``<br>attribute will not be available.<br><br>The refitted estimator is made available at the ``best_estimator_``<br>attribute and permits using ``predict`` directly on this<br>``GridSearchCV`` instance.<br><br>Also for multiple metric evaluation, the attributes ``best_index_``,<br>``best_score_`` and ``best_params_`` will only be available if<br>``refit`` is set and all of them will be determined w.r.t this specific<br>scorer.<br><br>See ``scoring`` parameter to know more about multiple metric<br>evaluation.<br><br>See :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_digits.py`<br>to see how to design a custom selection strategy using a callable<br>via `refit`.<br><br>See :ref:`this example<br><sphx_glr_auto_examples_model_selection_plot_grid_search_refit_callable.py>`<br>for an example of how to use ``refit=callable`` to balance model<br>complexity and cross-validated score.<br><br>.. versionchanged:: 0.20<br>    Support for callable added.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cv',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=cv,-int%2C%20cross-validation%20generator%20or%20an%20iterable%2C%20default%3DNone\">\n",
+       "            cv\n",
+       "            <span class=\"param-doc-description\">cv: int, cross-validation generator or an iterable, default=None<br><br>Determines the cross-validation splitting strategy.<br>Possible inputs for cv are:<br><br>- None, to use the default 5-fold cross validation,<br>- integer, to specify the number of folds in a `(Stratified)KFold`,<br>- :term:`CV splitter`,<br>- An iterable yielding (train, test) splits as arrays of indices.<br><br>For integer/None inputs, if the estimator is a classifier and ``y`` is<br>either binary or multiclass, :class:`StratifiedKFold` is used. In all<br>other cases, :class:`KFold` is used. These splitters are instantiated<br>with `shuffle=False` so the splits will be the same across calls.<br><br>Refer :ref:`User Guide <cross_validation>` for the various<br>cross-validation strategies that can be used here.<br><br>.. versionchanged:: 0.22<br>    ``cv`` default value if None changed from 3-fold to 5-fold.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">10</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=verbose,-int\">\n",
+       "            verbose\n",
+       "            <span class=\"param-doc-description\">verbose: int<br><br>Controls the verbosity: the higher, the more messages.<br><br>- >1 : the computation time for each fold and parameter candidate is<br>  displayed;<br>- >2 : the score is also displayed;<br>- >3 : the fold and candidate parameter indexes are also displayed<br>  together with the starting time of the computation.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('pre_dispatch',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=pre_dispatch,-int%2C%20or%20str%2C%20default%3D%272%2An_jobs%27\">\n",
+       "            pre_dispatch\n",
+       "            <span class=\"param-doc-description\">pre_dispatch: int, or str, default='2*n_jobs'<br><br>Controls the number of jobs that get dispatched during parallel<br>execution. Reducing this number can be useful to avoid an<br>explosion of memory consumption when more jobs get dispatched<br>than CPUs can process. This parameter can be:<br><br>- None, in which case all the jobs are immediately created and spawned. Use<br>  this for lightweight and fast-running jobs, to avoid delays due to on-demand<br>  spawning of the jobs<br>- An int, giving the exact number of total jobs that are spawned<br>- A str, giving an expression as a function of n_jobs, as in '2*n_jobs'</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;2*n_jobs&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('error_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=error_score,-%27raise%27%20or%20numeric%2C%20default%3Dnp.nan\">\n",
+       "            error_score\n",
+       "            <span class=\"param-doc-description\">error_score: 'raise' or numeric, default=np.nan<br><br>Value to assign to the score if an error occurs in estimator fitting.<br>If set to 'raise', the error is raised. If a numeric value is given,<br>FitFailedWarning is raised. This parameter does not affect the refit<br>step, which will always raise the error.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">nan</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_train_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.model_selection.GridSearchCV.html#:~:text=return_train_score,-bool%2C%20default%3DFalse\">\n",
+       "            return_train_score\n",
+       "            <span class=\"param-doc-description\">return_train_score: bool, default=False<br><br>If ``False``, the ``cv_results_`` attribute will not include training<br>scores.<br>Computing training scores is used to get insights on how different<br>parameter settings impact the overfitting/underfitting trade-off.<br>However computing the scores on the training set can be computationally<br>expensive and is not strictly required to select the parameters that<br>yield the best generalization performance.<br><br>.. versionadded:: 0.19<br><br>.. versionchanged:: 0.21<br>    Default value was changed from ``True`` to ``False``</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>best_estimator_: KNeighborsClassifier</div></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___\"><pre>KNeighborsClassifier(n_neighbors=7)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_neighbors',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_neighbors,-int%2C%20default%3D5\">\n",
+       "            n_neighbors\n",
+       "            <span class=\"param-doc-description\">n_neighbors: int, default=5<br><br>Number of neighbors to use by default for :meth:`kneighbors` queries.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">7</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=weights,-%7B%27uniform%27%2C%20%27distance%27%7D%2C%20callable%20or%20None%2C%20default%3D%27uniform%27\">\n",
+       "            weights\n",
+       "            <span class=\"param-doc-description\">weights: {'uniform', 'distance'}, callable or None, default='uniform'<br><br>Weight function used in prediction.  Possible values:<br><br>- 'uniform' : uniform weights.  All points in each neighborhood<br>  are weighted equally.<br>- 'distance' : weight points by the inverse of their distance.<br>  in this case, closer neighbors of a query point will have a<br>  greater influence than neighbors which are further away.<br>- [callable] : a user-defined function which accepts an<br>  array of distances, and returns an array of the same shape<br>  containing the weights.<br><br>Refer to the example entitled<br>:ref:`sphx_glr_auto_examples_neighbors_plot_classification.py`<br>showing the impact of the `weights` parameter on the decision<br>boundary.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('algorithm',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=algorithm,-%7B%27auto%27%2C%20%27ball_tree%27%2C%20%27kd_tree%27%2C%20%27brute%27%7D%2C%20default%3D%27auto%27\">\n",
+       "            algorithm\n",
+       "            <span class=\"param-doc-description\">algorithm: {'auto', 'ball_tree', 'kd_tree', 'brute'}, default='auto'<br><br>Algorithm used to compute the nearest neighbors:<br><br>- 'ball_tree' will use :class:`BallTree`<br>- 'kd_tree' will use :class:`KDTree`<br>- 'brute' will use a brute-force search.<br>- 'auto' will attempt to decide the most appropriate algorithm<br>  based on the values passed to :meth:`fit` method.<br><br>Note: fitting on sparse input will override the setting of<br>this parameter, using brute force.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('leaf_size',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=leaf_size,-int%2C%20default%3D30\">\n",
+       "            leaf_size\n",
+       "            <span class=\"param-doc-description\">leaf_size: int, default=30<br><br>Leaf size passed to BallTree or KDTree.  This can affect the<br>speed of the construction and query, as well as the memory<br>required to store the tree.  The optimal value depends on the<br>nature of the problem.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('p',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=p,-float%2C%20default%3D2\">\n",
+       "            p\n",
+       "            <span class=\"param-doc-description\">p: float, default=2<br><br>Power parameter for the Minkowski metric. When p = 1, this is equivalent<br>to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2.<br>For arbitrary p, minkowski_distance (l_p) is used. This parameter is expected<br>to be positive.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric,-str%20or%20callable%2C%20default%3D%27minkowski%27\">\n",
+       "            metric\n",
+       "            <span class=\"param-doc-description\">metric: str or callable, default='minkowski'<br><br>Metric to use for distance computation. Default is \"minkowski\", which<br>results in the standard Euclidean distance when p = 2. See the<br>documentation of `scipy.spatial.distance<br><https://docs.scipy.org/doc/scipy/reference/spatial.distance.html>`_ and<br>the metrics listed in<br>:class:`~sklearn.metrics.pairwise.distance_metrics` for valid metric<br>values.<br><br>If metric is \"precomputed\", X is assumed to be a distance matrix and<br>must be square during fit. X may be a :term:`sparse graph`, in which<br>case only \"nonzero\" elements may be considered neighbors.<br><br>If metric is a callable function, it takes two arrays representing 1D<br>vectors as inputs and must return one value indicating the distance<br>between those vectors. This works for Scipy's metrics, but is less<br>efficient than passing the metric name as a string.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric_params,-dict%2C%20default%3DNone\">\n",
+       "            metric_params\n",
+       "            <span class=\"param-doc-description\">metric_params: dict, default=None<br><br>Additional keyword arguments for the metric function.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_jobs,-int%2C%20default%3DNone\">\n",
+       "            n_jobs\n",
+       "            <span class=\"param-doc-description\">n_jobs: int, default=None<br><br>The number of parallel jobs to run for neighbors search.<br>``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.<br>``-1`` means using all processors. See :term:`Glossary <n_jobs>`<br>for more details.<br>Doesn't affect :meth:`fit` method.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div></div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.copy-paste-icon').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling\n",
+       "        .textContent.trim().split(' ')[0];\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "\n",
+       "\n",
+       "/**\n",
+       " * Adapted from Skrub\n",
+       " * https://github.com/skrub-data/skrub/blob/403466d1d5d4dc76a7ef569b3f8228db59a31dc3/skrub/_reporting/_data/templates/report.js#L789\n",
+       " * @returns \"light\" or \"dark\"\n",
+       " */\n",
+       "function detectTheme(element) {\n",
+       "    const body = document.querySelector('body');\n",
+       "\n",
+       "    // Check VSCode theme\n",
+       "    const themeKindAttr = body.getAttribute('data-vscode-theme-kind');\n",
+       "    const themeNameAttr = body.getAttribute('data-vscode-theme-name');\n",
+       "\n",
+       "    if (themeKindAttr && themeNameAttr) {\n",
+       "        const themeKind = themeKindAttr.toLowerCase();\n",
+       "        const themeName = themeNameAttr.toLowerCase();\n",
+       "\n",
+       "        if (themeKind.includes(\"dark\") || themeName.includes(\"dark\")) {\n",
+       "            return \"dark\";\n",
+       "        }\n",
+       "        if (themeKind.includes(\"light\") || themeName.includes(\"light\")) {\n",
+       "            return \"light\";\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    // Check Jupyter theme\n",
+       "    if (body.getAttribute('data-jp-theme-light') === 'false') {\n",
+       "        return 'dark';\n",
+       "    } else if (body.getAttribute('data-jp-theme-light') === 'true') {\n",
+       "        return 'light';\n",
+       "    }\n",
+       "\n",
+       "    // Guess based on a parent element's color\n",
+       "    const color = window.getComputedStyle(element.parentNode, null).getPropertyValue('color');\n",
+       "    const match = color.match(/^rgb\\s*\\(\\s*(\\d+)\\s*,\\s*(\\d+)\\s*,\\s*(\\d+)\\s*\\)\\s*$/i);\n",
+       "    if (match) {\n",
+       "        const [r, g, b] = [\n",
+       "            parseFloat(match[1]),\n",
+       "            parseFloat(match[2]),\n",
+       "            parseFloat(match[3])\n",
+       "        ];\n",
+       "\n",
+       "        // https://en.wikipedia.org/wiki/HSL_and_HSV#Lightness\n",
+       "        const luma = 0.299 * r + 0.587 * g + 0.114 * b;\n",
+       "\n",
+       "        if (luma > 180) {\n",
+       "            // If the text is very bright we have a dark theme\n",
+       "            return 'dark';\n",
+       "        }\n",
+       "        if (luma < 75) {\n",
+       "            // If the text is very dark we have a light theme\n",
+       "            return 'light';\n",
+       "        }\n",
+       "        // Otherwise fall back to the next heuristic.\n",
+       "    }\n",
+       "\n",
+       "    // Fallback to system preference\n",
+       "    return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';\n",
+       "}\n",
+       "\n",
+       "\n",
+       "function forceTheme(elementId) {\n",
+       "    const estimatorElement = document.querySelector(`#${elementId}`);\n",
+       "    if (estimatorElement === null) {\n",
+       "        console.error(`Element with id ${elementId} not found.`);\n",
+       "    } else {\n",
+       "        const theme = detectTheme(estimatorElement);\n",
+       "        estimatorElement.classList.add(theme);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "forceTheme('sk-container-id-1');</script></body>"
+      ],
+      "text/plain": [
+       "GridSearchCV(cv=10, estimator=KNeighborsClassifier(),\n",
+       "             param_grid={'n_neighbors': range(1, 51)})"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 4.1 Fit model on training data.\n",
     "grid_search.fit(X_train, y_train)"
@@ -396,10 +2080,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "721f7423",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'n_neighbors': 7}"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 4.2 Return the best n_neighbours\n",
     "grid_search.best_params_\n",
@@ -419,10 +2114,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "ffefa9f2",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "7"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# assign the best k from grid search to a variable\n",
     "best_k = grid_search.best_params_[\"n_neighbors\"]\n",
@@ -431,7 +2137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "f958b9e6",
    "metadata": {},
    "outputs": [],
@@ -442,10 +2148,827 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "6ea7d9b2",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2.light {\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: black;\n",
+       "  --sklearn-color-background: white;\n",
+       "  --sklearn-color-border-box: black;\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2.dark {\n",
+       "  --sklearn-color-text-on-default-background: white;\n",
+       "  --sklearn-color-background: #111;\n",
+       "  --sklearn-color-border-box: white;\n",
+       "  --sklearn-color-icon: #878787;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: center;\n",
+       "  justify-content: center;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-3) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-0);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  border: var(--sklearn-color-fitted-level-0) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-0);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table {\n",
+       "    font-family: monospace;\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary::marker {\n",
+       "    font-size: 0.7rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "    margin-top: 0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       "/*\n",
+       "    `table td`is set in notebook with right text-align.\n",
+       "    We need to overwrite it.\n",
+       "*/\n",
+       ".estimator-table table td.param {\n",
+       "    text-align: left;\n",
+       "    position: relative;\n",
+       "    padding: 0;\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left !important;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    background-color: transparent;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left !important;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       "/*\n",
+       "    Styles for parameter documentation links\n",
+       "    We need styling for visited so jupyter doesn't overwrite it\n",
+       "*/\n",
+       "a.param-doc-link,\n",
+       "a.param-doc-link:link,\n",
+       "a.param-doc-link:visited {\n",
+       "    text-decoration: underline dashed;\n",
+       "    text-underline-offset: .3em;\n",
+       "    color: inherit;\n",
+       "    display: block;\n",
+       "    padding: .5em;\n",
+       "}\n",
+       "\n",
+       "/* \"hack\" to make the entire area of the cell containing the link clickable */\n",
+       "a.param-doc-link::before {\n",
+       "    position: absolute;\n",
+       "    content: \"\";\n",
+       "    inset: 0;\n",
+       "}\n",
+       "\n",
+       ".param-doc-description {\n",
+       "    display: none;\n",
+       "    position: absolute;\n",
+       "    z-index: 9999;\n",
+       "    left: 0;\n",
+       "    padding: .5ex;\n",
+       "    margin-left: 1.5em;\n",
+       "    color: var(--sklearn-color-text);\n",
+       "    box-shadow: .3em .3em .4em #999;\n",
+       "    width: max-content;\n",
+       "    text-align: left;\n",
+       "    max-height: 10em;\n",
+       "    overflow-y: auto;\n",
+       "\n",
+       "    /* unfitted */\n",
+       "    background: var(--sklearn-color-unfitted-level-0);\n",
+       "    border: thin solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       "/* Fitted state for parameter tooltips */\n",
+       ".fitted .param-doc-description {\n",
+       "    /* fitted */\n",
+       "    background: var(--sklearn-color-fitted-level-0);\n",
+       "    border: thin solid var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".param-doc-link:hover .param-doc-description {\n",
+       "    display: block;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=7)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_neighbors',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_neighbors,-int%2C%20default%3D5\">\n",
+       "            n_neighbors\n",
+       "            <span class=\"param-doc-description\">n_neighbors: int, default=5<br><br>Number of neighbors to use by default for :meth:`kneighbors` queries.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">7</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=weights,-%7B%27uniform%27%2C%20%27distance%27%7D%2C%20callable%20or%20None%2C%20default%3D%27uniform%27\">\n",
+       "            weights\n",
+       "            <span class=\"param-doc-description\">weights: {'uniform', 'distance'}, callable or None, default='uniform'<br><br>Weight function used in prediction.  Possible values:<br><br>- 'uniform' : uniform weights.  All points in each neighborhood<br>  are weighted equally.<br>- 'distance' : weight points by the inverse of their distance.<br>  in this case, closer neighbors of a query point will have a<br>  greater influence than neighbors which are further away.<br>- [callable] : a user-defined function which accepts an<br>  array of distances, and returns an array of the same shape<br>  containing the weights.<br><br>Refer to the example entitled<br>:ref:`sphx_glr_auto_examples_neighbors_plot_classification.py`<br>showing the impact of the `weights` parameter on the decision<br>boundary.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('algorithm',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=algorithm,-%7B%27auto%27%2C%20%27ball_tree%27%2C%20%27kd_tree%27%2C%20%27brute%27%7D%2C%20default%3D%27auto%27\">\n",
+       "            algorithm\n",
+       "            <span class=\"param-doc-description\">algorithm: {'auto', 'ball_tree', 'kd_tree', 'brute'}, default='auto'<br><br>Algorithm used to compute the nearest neighbors:<br><br>- 'ball_tree' will use :class:`BallTree`<br>- 'kd_tree' will use :class:`KDTree`<br>- 'brute' will use a brute-force search.<br>- 'auto' will attempt to decide the most appropriate algorithm<br>  based on the values passed to :meth:`fit` method.<br><br>Note: fitting on sparse input will override the setting of<br>this parameter, using brute force.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('leaf_size',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=leaf_size,-int%2C%20default%3D30\">\n",
+       "            leaf_size\n",
+       "            <span class=\"param-doc-description\">leaf_size: int, default=30<br><br>Leaf size passed to BallTree or KDTree.  This can affect the<br>speed of the construction and query, as well as the memory<br>required to store the tree.  The optimal value depends on the<br>nature of the problem.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('p',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=p,-float%2C%20default%3D2\">\n",
+       "            p\n",
+       "            <span class=\"param-doc-description\">p: float, default=2<br><br>Power parameter for the Minkowski metric. When p = 1, this is equivalent<br>to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2.<br>For arbitrary p, minkowski_distance (l_p) is used. This parameter is expected<br>to be positive.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric,-str%20or%20callable%2C%20default%3D%27minkowski%27\">\n",
+       "            metric\n",
+       "            <span class=\"param-doc-description\">metric: str or callable, default='minkowski'<br><br>Metric to use for distance computation. Default is \"minkowski\", which<br>results in the standard Euclidean distance when p = 2. See the<br>documentation of `scipy.spatial.distance<br><https://docs.scipy.org/doc/scipy/reference/spatial.distance.html>`_ and<br>the metrics listed in<br>:class:`~sklearn.metrics.pairwise.distance_metrics` for valid metric<br>values.<br><br>If metric is \"precomputed\", X is assumed to be a distance matrix and<br>must be square during fit. X may be a :term:`sparse graph`, in which<br>case only \"nonzero\" elements may be considered neighbors.<br><br>If metric is a callable function, it takes two arrays representing 1D<br>vectors as inputs and must return one value indicating the distance<br>between those vectors. This works for Scipy's metrics, but is less<br>efficient than passing the metric name as a string.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=metric_params,-dict%2C%20default%3DNone\">\n",
+       "            metric_params\n",
+       "            <span class=\"param-doc-description\">metric_params: dict, default=None<br><br>Additional keyword arguments for the metric function.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">\n",
+       "        <a class=\"param-doc-link\"\n",
+       "            rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.8/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#:~:text=n_jobs,-int%2C%20default%3DNone\">\n",
+       "            n_jobs\n",
+       "            <span class=\"param-doc-description\">n_jobs: int, default=None<br><br>The number of parallel jobs to run for neighbors search.<br>``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.<br>``-1`` means using all processors. See :term:`Glossary <n_jobs>`<br>for more details.<br>Doesn't affect :meth:`fit` method.</span>\n",
+       "        </a>\n",
+       "    </td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
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+       "\n",
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+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=7)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# fit the model on training data\n",
     "knn_final.fit(X_train, y_train)"
@@ -453,10 +2976,1058 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "fdb01d9b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
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+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "      <th>predicted_class</th>\n",
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+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>102</th>\n",
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+       "      <td>-0.734657</td>\n",
+       "      <td>0.661468</td>\n",
+       "      <td>-0.722540</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
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+       "      <th>96</th>\n",
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+       "      <td>-0.388168</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
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+       "      <th>65</th>\n",
+       "      <td>-0.778980</td>\n",
+       "      <td>-1.011081</td>\n",
+       "      <td>0.707247</td>\n",
+       "      <td>-0.418881</td>\n",
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+       "      <td>-0.440238</td>\n",
+       "      <td>-0.219390</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
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+       "      <th>79</th>\n",
+       "      <td>-0.371343</td>\n",
+       "      <td>1.376703</td>\n",
+       "      <td>0.122392</td>\n",
+       "      <td>1.052516</td>\n",
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+       "      <td>-0.904056</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1.024507</td>\n",
+       "      <td>-0.687923</td>\n",
+       "      <td>0.926567</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.071345</td>\n",
+       "      <td>1.049347</td>\n",
+       "      <td>1.376168</td>\n",
+       "      <td>0.307374</td>\n",
+       "      <td>0.226196</td>\n",
+       "      <td>0.666984</td>\n",
+       "      <td>0.757038</td>\n",
+       "      <td>-0.058878</td>\n",
+       "      <td>1.220001</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>109</th>\n",
+       "      <td>-1.717782</td>\n",
+       "      <td>-0.885409</td>\n",
+       "      <td>1.218995</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>-0.403135</td>\n",
+       "      <td>0.712858</td>\n",
+       "      <td>0.894264</td>\n",
+       "      <td>-0.578985</td>\n",
+       "      <td>1.575301</td>\n",
+       "      <td>-1.041667</td>\n",
+       "      <td>0.011190</td>\n",
+       "      <td>0.915707</td>\n",
+       "      <td>-0.213021</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>113</th>\n",
+       "      <td>-1.964835</td>\n",
+       "      <td>-1.432983</td>\n",
+       "      <td>0.487926</td>\n",
+       "      <td>0.451946</td>\n",
+       "      <td>-0.824415</td>\n",
+       "      <td>0.296251</td>\n",
+       "      <td>-0.019346</td>\n",
+       "      <td>0.468530</td>\n",
+       "      <td>-0.264388</td>\n",
+       "      <td>-0.855662</td>\n",
+       "      <td>0.625418</td>\n",
+       "      <td>-0.426113</td>\n",
+       "      <td>-0.996407</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1.073917</td>\n",
+       "      <td>-0.391694</td>\n",
+       "      <td>1.584529</td>\n",
+       "      <td>-0.028510</td>\n",
+       "      <td>0.509638</td>\n",
+       "      <td>1.049347</td>\n",
+       "      <td>0.944462</td>\n",
+       "      <td>0.065639</td>\n",
+       "      <td>0.296279</td>\n",
+       "      <td>-0.241413</td>\n",
+       "      <td>1.283518</td>\n",
+       "      <td>1.113449</td>\n",
+       "      <td>0.535335</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>159</th>\n",
+       "      <td>0.592164</td>\n",
+       "      <td>-0.598156</td>\n",
+       "      <td>0.999674</td>\n",
+       "      <td>0.902373</td>\n",
+       "      <td>-0.754202</td>\n",
+       "      <td>0.488531</td>\n",
+       "      <td>-0.932956</td>\n",
+       "      <td>1.274310</td>\n",
+       "      <td>1.224884</td>\n",
+       "      <td>2.894719</td>\n",
+       "      <td>-1.699872</td>\n",
+       "      <td>-1.174708</td>\n",
+       "      <td>-0.404091</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>0.085705</td>\n",
+       "      <td>-0.750759</td>\n",
+       "      <td>-0.974210</td>\n",
+       "      <td>-1.199622</td>\n",
+       "      <td>-0.122282</td>\n",
+       "      <td>0.168065</td>\n",
+       "      <td>0.613153</td>\n",
+       "      <td>-0.659563</td>\n",
+       "      <td>-0.387033</td>\n",
+       "      <td>-0.587469</td>\n",
+       "      <td>0.976405</td>\n",
+       "      <td>0.110615</td>\n",
+       "      <td>0.869707</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>0.629222</td>\n",
+       "      <td>-0.481460</td>\n",
+       "      <td>1.036228</td>\n",
+       "      <td>-0.148624</td>\n",
+       "      <td>0.720278</td>\n",
+       "      <td>0.087948</td>\n",
+       "      <td>0.502717</td>\n",
+       "      <td>-0.578985</td>\n",
+       "      <td>-0.089179</td>\n",
+       "      <td>-0.371184</td>\n",
+       "      <td>0.625418</td>\n",
+       "      <td>0.364855</td>\n",
+       "      <td>1.108544</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>-1.149560</td>\n",
+       "      <td>-0.158301</td>\n",
+       "      <td>-0.718336</td>\n",
+       "      <td>0.451946</td>\n",
+       "      <td>-1.035055</td>\n",
+       "      <td>0.488531</td>\n",
+       "      <td>0.623193</td>\n",
+       "      <td>0.065639</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>-0.994085</td>\n",
+       "      <td>-0.427544</td>\n",
+       "      <td>0.943956</td>\n",
+       "      <td>-1.174738</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>115</th>\n",
+       "      <td>-2.434235</td>\n",
+       "      <td>-0.741782</td>\n",
+       "      <td>-0.608676</td>\n",
+       "      <td>0.602088</td>\n",
+       "      <td>-1.035055</td>\n",
+       "      <td>0.264205</td>\n",
+       "      <td>0.141289</td>\n",
+       "      <td>1.274310</td>\n",
+       "      <td>0.734300</td>\n",
+       "      <td>-1.366095</td>\n",
+       "      <td>3.301694</td>\n",
+       "      <td>0.364855</td>\n",
+       "      <td>-1.082388</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>71</th>\n",
+       "      <td>1.061565</td>\n",
+       "      <td>-0.741782</td>\n",
+       "      <td>1.109334</td>\n",
+       "      <td>1.653086</td>\n",
+       "      <td>-0.964842</td>\n",
+       "      <td>1.049347</td>\n",
+       "      <td>0.834026</td>\n",
+       "      <td>-1.223610</td>\n",
+       "      <td>0.489009</td>\n",
+       "      <td>-0.725891</td>\n",
+       "      <td>1.766126</td>\n",
+       "      <td>0.774463</td>\n",
+       "      <td>-1.072834</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>0.036295</td>\n",
+       "      <td>-1.289357</td>\n",
+       "      <td>-2.399793</td>\n",
+       "      <td>-1.049479</td>\n",
+       "      <td>-0.964842</td>\n",
+       "      <td>-0.552984</td>\n",
+       "      <td>0.000733</td>\n",
+       "      <td>-0.981875</td>\n",
+       "      <td>-0.229346</td>\n",
+       "      <td>-0.198156</td>\n",
+       "      <td>1.020278</td>\n",
+       "      <td>-0.185998</td>\n",
+       "      <td>-1.130155</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>-0.148995</td>\n",
+       "      <td>0.586759</td>\n",
+       "      <td>0.122392</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>0.298998</td>\n",
+       "      <td>-1.594500</td>\n",
+       "      <td>-0.812480</td>\n",
+       "      <td>-0.981875</td>\n",
+       "      <td>-1.333159</td>\n",
+       "      <td>0.147900</td>\n",
+       "      <td>-0.954024</td>\n",
+       "      <td>-1.683187</td>\n",
+       "      <td>-0.690695</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>0.938038</td>\n",
+       "      <td>-0.723829</td>\n",
+       "      <td>1.218995</td>\n",
+       "      <td>0.001518</td>\n",
+       "      <td>2.264972</td>\n",
+       "      <td>1.049347</td>\n",
+       "      <td>0.713550</td>\n",
+       "      <td>1.113154</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>0.147900</td>\n",
+       "      <td>1.283518</td>\n",
+       "      <td>0.548472</td>\n",
+       "      <td>1.554373</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>-0.828391</td>\n",
+       "      <td>-1.109824</td>\n",
+       "      <td>-0.316249</td>\n",
+       "      <td>-1.049479</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>-0.392751</td>\n",
+       "      <td>-0.942995</td>\n",
+       "      <td>2.160669</td>\n",
+       "      <td>-2.069034</td>\n",
+       "      <td>-0.773474</td>\n",
+       "      <td>1.283518</td>\n",
+       "      <td>-1.330077</td>\n",
+       "      <td>-0.213021</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0.789806</td>\n",
+       "      <td>0.685502</td>\n",
+       "      <td>0.707247</td>\n",
+       "      <td>-1.289707</td>\n",
+       "      <td>1.141558</td>\n",
+       "      <td>0.648764</td>\n",
+       "      <td>1.004700</td>\n",
+       "      <td>-1.545922</td>\n",
+       "      <td>0.121071</td>\n",
+       "      <td>0.018129</td>\n",
+       "      <td>0.011190</td>\n",
+       "      <td>1.056952</td>\n",
+       "      <td>0.312420</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>114</th>\n",
+       "      <td>-1.137207</td>\n",
+       "      <td>-0.849502</td>\n",
+       "      <td>0.487926</td>\n",
+       "      <td>0.902373</td>\n",
+       "      <td>-1.105268</td>\n",
+       "      <td>0.424438</td>\n",
+       "      <td>0.261765</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.965221</td>\n",
+       "      <td>-0.933525</td>\n",
+       "      <td>-0.120430</td>\n",
+       "      <td>0.816836</td>\n",
+       "      <td>-1.152447</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1.110975</td>\n",
+       "      <td>-0.589180</td>\n",
+       "      <td>-0.901103</td>\n",
+       "      <td>-1.049479</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>1.289697</td>\n",
+       "      <td>1.366128</td>\n",
+       "      <td>-1.223610</td>\n",
+       "      <td>0.962071</td>\n",
+       "      <td>0.450699</td>\n",
+       "      <td>-0.208177</td>\n",
+       "      <td>1.014578</td>\n",
+       "      <td>0.758249</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1.358028</td>\n",
+       "      <td>-0.283974</td>\n",
+       "      <td>0.122392</td>\n",
+       "      <td>-0.208681</td>\n",
+       "      <td>0.228785</td>\n",
+       "      <td>0.728881</td>\n",
+       "      <td>0.894264</td>\n",
+       "      <td>-0.337251</td>\n",
+       "      <td>1.382572</td>\n",
+       "      <td>0.493956</td>\n",
+       "      <td>0.493797</td>\n",
+       "      <td>0.195361</td>\n",
+       "      <td>0.997086</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>158</th>\n",
+       "      <td>1.654492</td>\n",
+       "      <td>-0.589180</td>\n",
+       "      <td>1.218995</td>\n",
+       "      <td>1.653086</td>\n",
+       "      <td>-0.122282</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>-0.722123</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>1.943238</td>\n",
+       "      <td>3.435432</td>\n",
+       "      <td>-1.699872</td>\n",
+       "      <td>-0.920468</td>\n",
+       "      <td>-0.276711</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>133</th>\n",
+       "      <td>-0.371343</td>\n",
+       "      <td>1.089450</td>\n",
+       "      <td>-0.023821</td>\n",
+       "      <td>0.602088</td>\n",
+       "      <td>0.439425</td>\n",
+       "      <td>-0.953567</td>\n",
+       "      <td>-0.832559</td>\n",
+       "      <td>-1.545922</td>\n",
+       "      <td>-1.315638</td>\n",
+       "      <td>-0.025128</td>\n",
+       "      <td>-0.778531</td>\n",
+       "      <td>-1.866805</td>\n",
+       "      <td>-0.467781</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>137</th>\n",
+       "      <td>-0.581338</td>\n",
+       "      <td>2.848870</td>\n",
+       "      <td>0.999674</td>\n",
+       "      <td>1.653086</td>\n",
+       "      <td>-0.262708</td>\n",
+       "      <td>-0.809357</td>\n",
+       "      <td>-1.434939</td>\n",
+       "      <td>2.160669</td>\n",
+       "      <td>-0.860096</td>\n",
+       "      <td>-0.025128</td>\n",
+       "      <td>-0.603037</td>\n",
+       "      <td>-1.301828</td>\n",
+       "      <td>-0.738463</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>154</th>\n",
+       "      <td>-0.519575</td>\n",
+       "      <td>-0.939268</td>\n",
+       "      <td>-0.974210</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>0.228785</td>\n",
+       "      <td>-1.306080</td>\n",
+       "      <td>-1.455019</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>-0.334471</td>\n",
+       "      <td>1.099554</td>\n",
+       "      <td>-1.655999</td>\n",
+       "      <td>-1.499570</td>\n",
+       "      <td>-0.340401</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>136</th>\n",
+       "      <td>-0.927212</td>\n",
+       "      <td>2.139716</td>\n",
+       "      <td>0.634140</td>\n",
+       "      <td>0.451946</td>\n",
+       "      <td>-0.754202</td>\n",
+       "      <td>-1.466313</td>\n",
+       "      <td>-1.565455</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>-1.385721</td>\n",
+       "      <td>-0.522583</td>\n",
+       "      <td>-0.910151</td>\n",
+       "      <td>-1.895054</td>\n",
+       "      <td>-0.085641</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.196879</td>\n",
+       "      <td>0.021231</td>\n",
+       "      <td>1.109334</td>\n",
+       "      <td>-0.268738</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.215533</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>2.135968</td>\n",
+       "      <td>0.269020</td>\n",
+       "      <td>0.318304</td>\n",
+       "      <td>0.788587</td>\n",
+       "      <td>1.395148</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>168</th>\n",
+       "      <td>0.715690</td>\n",
+       "      <td>0.218717</td>\n",
+       "      <td>1.182441</td>\n",
+       "      <td>1.502943</td>\n",
+       "      <td>0.369212</td>\n",
+       "      <td>-1.193917</td>\n",
+       "      <td>-1.193987</td>\n",
+       "      <td>0.226796</td>\n",
+       "      <td>-0.089179</td>\n",
+       "      <td>1.558078</td>\n",
+       "      <td>-0.954024</td>\n",
+       "      <td>-1.146459</td>\n",
+       "      <td>0.009893</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>-0.717217</td>\n",
+       "      <td>-0.652016</td>\n",
+       "      <td>-0.645229</td>\n",
+       "      <td>0.902373</td>\n",
+       "      <td>0.579852</td>\n",
+       "      <td>-0.472868</td>\n",
+       "      <td>0.060971</td>\n",
+       "      <td>-0.176095</td>\n",
+       "      <td>0.033467</td>\n",
+       "      <td>-1.296884</td>\n",
+       "      <td>0.449924</td>\n",
+       "      <td>0.491974</td>\n",
+       "      <td>-1.279827</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>0.839217</td>\n",
+       "      <td>-0.454530</td>\n",
+       "      <td>-0.023821</td>\n",
+       "      <td>-0.689137</td>\n",
+       "      <td>0.298998</td>\n",
+       "      <td>0.200111</td>\n",
+       "      <td>0.663351</td>\n",
+       "      <td>0.468530</td>\n",
+       "      <td>0.664217</td>\n",
+       "      <td>-0.526909</td>\n",
+       "      <td>1.195772</td>\n",
+       "      <td>0.364855</td>\n",
+       "      <td>0.774172</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>0.876275</td>\n",
+       "      <td>-0.427600</td>\n",
+       "      <td>-0.023821</td>\n",
+       "      <td>-0.869308</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>0.504554</td>\n",
+       "      <td>0.854105</td>\n",
+       "      <td>-0.740141</td>\n",
+       "      <td>0.173634</td>\n",
+       "      <td>-0.544212</td>\n",
+       "      <td>0.669291</td>\n",
+       "      <td>1.960915</td>\n",
+       "      <td>0.917474</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>108</th>\n",
+       "      <td>-0.964270</td>\n",
+       "      <td>-0.939268</td>\n",
+       "      <td>-1.559065</td>\n",
+       "      <td>-0.148624</td>\n",
+       "      <td>-0.543562</td>\n",
+       "      <td>0.103972</td>\n",
+       "      <td>0.010773</td>\n",
+       "      <td>0.226796</td>\n",
+       "      <td>0.856946</td>\n",
+       "      <td>-1.020039</td>\n",
+       "      <td>-0.427544</td>\n",
+       "      <td>0.576721</td>\n",
+       "      <td>-1.384915</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>73</th>\n",
+       "      <td>-0.013116</td>\n",
+       "      <td>-0.598156</td>\n",
+       "      <td>0.853460</td>\n",
+       "      <td>3.154511</td>\n",
+       "      <td>2.756465</td>\n",
+       "      <td>1.610163</td>\n",
+       "      <td>0.864145</td>\n",
+       "      <td>-1.223610</td>\n",
+       "      <td>0.646696</td>\n",
+       "      <td>-0.738868</td>\n",
+       "      <td>1.546759</td>\n",
+       "      <td>1.254694</td>\n",
+       "      <td>0.758249</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>77</th>\n",
+       "      <td>-1.433671</td>\n",
+       "      <td>0.496993</td>\n",
+       "      <td>-0.499016</td>\n",
+       "      <td>-0.448909</td>\n",
+       "      <td>0.860705</td>\n",
+       "      <td>-0.921521</td>\n",
+       "      <td>-0.712083</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-1.122909</td>\n",
+       "      <td>-1.041667</td>\n",
+       "      <td>0.011190</td>\n",
+       "      <td>-0.129500</td>\n",
+       "      <td>-0.786230</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>142</th>\n",
+       "      <td>0.641574</td>\n",
+       "      <td>0.748338</td>\n",
+       "      <td>1.292101</td>\n",
+       "      <td>1.202658</td>\n",
+       "      <td>-0.192495</td>\n",
+       "      <td>-1.193917</td>\n",
+       "      <td>-1.515257</td>\n",
+       "      <td>1.113154</td>\n",
+       "      <td>-1.823742</td>\n",
+       "      <td>-0.306298</td>\n",
+       "      <td>-0.295924</td>\n",
+       "      <td>-0.779224</td>\n",
+       "      <td>-0.722540</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1.061565</td>\n",
+       "      <td>-0.885409</td>\n",
+       "      <td>-0.352802</td>\n",
+       "      <td>-1.049479</td>\n",
+       "      <td>-0.122282</td>\n",
+       "      <td>1.097417</td>\n",
+       "      <td>1.125176</td>\n",
+       "      <td>-1.143031</td>\n",
+       "      <td>0.453967</td>\n",
+       "      <td>0.935177</td>\n",
+       "      <td>0.230557</td>\n",
+       "      <td>1.325316</td>\n",
+       "      <td>0.949319</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85</th>\n",
+       "      <td>-0.408401</td>\n",
+       "      <td>-1.217544</td>\n",
+       "      <td>-0.462462</td>\n",
+       "      <td>-0.448909</td>\n",
+       "      <td>-0.052068</td>\n",
+       "      <td>-0.152402</td>\n",
+       "      <td>-0.089624</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>-0.229346</td>\n",
+       "      <td>-1.054644</td>\n",
+       "      <td>1.195772</td>\n",
+       "      <td>0.774463</td>\n",
+       "      <td>-0.945455</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>0.888627</td>\n",
+       "      <td>-0.813595</td>\n",
+       "      <td>0.487926</td>\n",
+       "      <td>-0.839280</td>\n",
+       "      <td>0.579852</td>\n",
+       "      <td>1.770396</td>\n",
+       "      <td>1.647239</td>\n",
+       "      <td>-1.384766</td>\n",
+       "      <td>0.786863</td>\n",
+       "      <td>0.753498</td>\n",
+       "      <td>-0.295924</td>\n",
+       "      <td>0.364855</td>\n",
+       "      <td>1.713598</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1.493907</td>\n",
+       "      <td>1.529305</td>\n",
+       "      <td>0.268606</td>\n",
+       "      <td>-0.178653</td>\n",
+       "      <td>0.790492</td>\n",
+       "      <td>0.889114</td>\n",
+       "      <td>0.623193</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>-0.597284</td>\n",
+       "      <td>0.078689</td>\n",
+       "      <td>-0.383670</td>\n",
+       "      <td>1.014578</td>\n",
+       "      <td>1.060776</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>0.332758</td>\n",
+       "      <td>1.744744</td>\n",
+       "      <td>-0.389355</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.422412</td>\n",
+       "      <td>-1.129824</td>\n",
+       "      <td>-1.344582</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>2.224236</td>\n",
+       "      <td>-1.612125</td>\n",
+       "      <td>-1.485445</td>\n",
+       "      <td>0.280575</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>1.086270</td>\n",
+       "      <td>-0.400670</td>\n",
+       "      <td>0.816907</td>\n",
+       "      <td>-1.349764</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>1.530047</td>\n",
+       "      <td>1.536802</td>\n",
+       "      <td>-1.545922</td>\n",
+       "      <td>0.191154</td>\n",
+       "      <td>0.160877</td>\n",
+       "      <td>-0.339797</td>\n",
+       "      <td>1.339440</td>\n",
+       "      <td>1.108544</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>143</th>\n",
+       "      <td>0.765101</td>\n",
+       "      <td>2.346179</td>\n",
+       "      <td>-0.060375</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>-0.543562</td>\n",
+       "      <td>-0.472868</td>\n",
+       "      <td>-1.234146</td>\n",
+       "      <td>0.871420</td>\n",
+       "      <td>-1.000263</td>\n",
+       "      <td>-0.284670</td>\n",
+       "      <td>-0.208177</td>\n",
+       "      <td>-0.793348</td>\n",
+       "      <td>-0.627005</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>1.395086</td>\n",
+       "      <td>1.583165</td>\n",
+       "      <td>1.365208</td>\n",
+       "      <td>1.502943</td>\n",
+       "      <td>-0.262708</td>\n",
+       "      <td>-0.392751</td>\n",
+       "      <td>-1.274305</td>\n",
+       "      <td>1.596623</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>1.791666</td>\n",
+       "      <td>-1.524378</td>\n",
+       "      <td>-1.428948</td>\n",
+       "      <td>-0.595160</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+       "102 -0.816038    0.102021  0.341713           0.451946  -0.122282   \n",
+       "84  -1.433671   -1.298334  0.780354          -0.448909  -0.403135   \n",
+       "96  -1.470729   -0.194208  1.365208           0.602088   2.405399   \n",
+       "65  -0.778980   -1.011081  0.707247          -0.418881  -0.122282   \n",
+       "79  -0.371343    1.376703  0.122392           1.052516   0.088358   \n",
+       "17   1.024507   -0.687923  0.926567           0.151661   1.071345   \n",
+       "109 -1.717782   -0.885409  1.218995           0.151661  -0.403135   \n",
+       "113 -1.964835   -1.432983  0.487926           0.451946  -0.824415   \n",
+       "28   1.073917   -0.391694  1.584529          -0.028510   0.509638   \n",
+       "159  0.592164   -0.598156  0.999674           0.902373  -0.754202   \n",
+       "38   0.085705   -0.750759 -0.974210          -1.199622  -0.122282   \n",
+       "34   0.629222   -0.481460  1.036228          -0.148624   0.720278   \n",
+       "125 -1.149560   -0.158301 -0.718336           0.451946  -1.035055   \n",
+       "115 -2.434235   -0.741782 -0.608676           0.602088  -1.035055   \n",
+       "71   1.061565   -0.741782  1.109334           1.653086  -0.964842   \n",
+       "76   0.036295   -1.289357 -2.399793          -1.049479  -0.964842   \n",
+       "131 -0.148995    0.586759  0.122392           0.151661   0.298998   \n",
+       "33   0.938038   -0.723829  1.218995           0.001518   2.264972   \n",
+       "60  -0.828391   -1.109824 -0.316249          -1.049479   0.088358   \n",
+       "19   0.789806    0.685502  0.707247          -1.289707   1.141558   \n",
+       "114 -1.137207   -0.849502  0.487926           0.902373  -1.105268   \n",
+       "47   1.110975   -0.589180 -0.901103          -1.049479   0.088358   \n",
+       "48   1.358028   -0.283974  0.122392          -0.208681   0.228785   \n",
+       "158  1.654492   -0.589180  1.218995           1.653086  -0.122282   \n",
+       "133 -0.371343    1.089450 -0.023821           0.602088   0.439425   \n",
+       "137 -0.581338    2.848870  0.999674           1.653086  -0.262708   \n",
+       "154 -0.519575   -0.939268 -0.974210           0.151661   0.228785   \n",
+       "136 -0.927212    2.139716  0.634140           0.451946  -0.754202   \n",
+       "2    0.196879    0.021231  1.109334          -0.268738   0.088358   \n",
+       "168  0.715690    0.218717  1.182441           1.502943   0.369212   \n",
+       "117 -0.717217   -0.652016 -0.645229           0.902373   0.579852   \n",
+       "32   0.839217   -0.454530 -0.023821          -0.689137   0.298998   \n",
+       "22   0.876275   -0.427600 -0.023821          -0.869308   0.088358   \n",
+       "108 -0.964270   -0.939268 -1.559065          -0.148624  -0.543562   \n",
+       "73  -0.013116   -0.598156  0.853460           3.154511   2.756465   \n",
+       "77  -1.433671    0.496993 -0.499016          -0.448909   0.860705   \n",
+       "142  0.641574    0.748338  1.292101           1.202658  -0.192495   \n",
+       "9    1.061565   -0.885409 -0.352802          -1.049479  -0.122282   \n",
+       "85  -0.408401   -1.217544 -0.462462          -0.448909  -0.052068   \n",
+       "58   0.888627   -0.813595  0.487926          -0.839280   0.579852   \n",
+       "45   1.493907    1.529305  0.268606          -0.178653   0.790492   \n",
+       "175  0.332758    1.744744 -0.389355           0.151661   1.422412   \n",
+       "42   1.086270   -0.400670  0.816907          -1.349764   0.088358   \n",
+       "143  0.765101    2.346179 -0.060375           0.151661  -0.543562   \n",
+       "177  1.395086    1.583165  1.365208           1.502943  -0.262708   \n",
+       "\n",
+       "     total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+       "102       0.424438    0.081051             -0.176095        -0.492158   \n",
+       "84       -0.152402    0.181447             -1.143031         1.330009   \n",
+       "96       -1.113800   -1.043392             -1.787656        -0.054137   \n",
+       "65        0.200111    0.623193              0.065639         0.856946   \n",
+       "79        0.857067    0.522796              0.549108         0.629175   \n",
+       "17        1.049347    1.376168              0.307374         0.226196   \n",
+       "109       0.712858    0.894264             -0.578985         1.575301   \n",
+       "113       0.296251   -0.019346              0.468530        -0.264388   \n",
+       "28        1.049347    0.944462              0.065639         0.296279   \n",
+       "159       0.488531   -0.932956              1.274310         1.224884   \n",
+       "38        0.168065    0.613153             -0.659563        -0.387033   \n",
+       "34        0.087948    0.502717             -0.578985        -0.089179   \n",
+       "125       0.488531    0.623193              0.065639        -0.422075   \n",
+       "115       0.264205    0.141289              1.274310         0.734300   \n",
+       "71        1.049347    0.834026             -1.223610         0.489009   \n",
+       "76       -0.552984    0.000733             -0.981875        -0.229346   \n",
+       "131      -1.594500   -0.812480             -0.981875        -1.333159   \n",
+       "33        1.049347    0.713550              1.113154        -0.422075   \n",
+       "60       -0.392751   -0.942995              2.160669        -2.069034   \n",
+       "19        0.648764    1.004700             -1.545922         0.121071   \n",
+       "114       0.424438    0.261765              0.549108        -0.965221   \n",
+       "47        1.289697    1.366128             -1.223610         0.962071   \n",
+       "48        0.728881    0.894264             -0.337251         1.382572   \n",
+       "158       0.808997   -0.722123              1.354888         1.943238   \n",
+       "133      -0.953567   -0.832559             -1.545922        -1.315638   \n",
+       "137      -0.809357   -1.434939              2.160669        -0.860096   \n",
+       "154      -1.306080   -1.455019              1.354888        -0.334471   \n",
+       "136      -1.466313   -1.565455              1.354888        -1.385721   \n",
+       "2         0.808997    1.215533             -0.498407         2.135968   \n",
+       "168      -1.193917   -1.193987              0.226796        -0.089179   \n",
+       "117      -0.472868    0.060971             -0.176095         0.033467   \n",
+       "32        0.200111    0.663351              0.468530         0.664217   \n",
+       "22        0.504554    0.854105             -0.740141         0.173634   \n",
+       "108       0.103972    0.010773              0.226796         0.856946   \n",
+       "73        1.610163    0.864145             -1.223610         0.646696   \n",
+       "77       -0.921521   -0.712083              0.549108        -1.122909   \n",
+       "142      -1.193917   -1.515257              1.113154        -1.823742   \n",
+       "9         1.097417    1.125176             -1.143031         0.453967   \n",
+       "85       -0.152402   -0.089624             -0.498407        -0.229346   \n",
+       "58        1.770396    1.647239             -1.384766         0.786863   \n",
+       "45        0.889114    0.623193             -0.498407        -0.597284   \n",
+       "175      -1.129824   -1.344582              0.549108        -0.422075   \n",
+       "42        1.530047    1.536802             -1.545922         0.191154   \n",
+       "143      -0.472868   -1.234146              0.871420        -1.000263   \n",
+       "177      -0.392751   -1.274305              1.596623        -0.422075   \n",
+       "\n",
+       "     color_intensity       hue  od280/od315_of_diluted_wines   proline  class  \\\n",
+       "102        -0.976782 -0.690784                      1.085200 -0.983669      1   \n",
+       "84         -0.868639 -0.734657                      0.661468 -0.722540      1   \n",
+       "96         -1.106553 -0.032683                     -0.496736 -0.388168      1   \n",
+       "65         -0.198156  1.020278                     -0.440238 -0.219390      1   \n",
+       "79         -1.076273  1.020278                      0.732090 -0.904056      1   \n",
+       "17          0.666984  0.757038                     -0.058878  1.220001      0   \n",
+       "109        -1.041667  0.011190                      0.915707 -0.213021      1   \n",
+       "113        -0.855662  0.625418                     -0.426113 -0.996407      1   \n",
+       "28         -0.241413  1.283518                      1.113449  0.535335      0   \n",
+       "159         2.894719 -1.699872                     -1.174708 -0.404091      2   \n",
+       "38         -0.587469  0.976405                      0.110615  0.869707      0   \n",
+       "34         -0.371184  0.625418                      0.364855  1.108544      0   \n",
+       "125        -0.994085 -0.427544                      0.943956 -1.174738      1   \n",
+       "115        -1.366095  3.301694                      0.364855 -1.082388      1   \n",
+       "71         -0.725891  1.766126                      0.774463 -1.072834      1   \n",
+       "76         -0.198156  1.020278                     -0.185998 -1.130155      1   \n",
+       "131         0.147900 -0.954024                     -1.683187 -0.690695      2   \n",
+       "33          0.147900  1.283518                      0.548472  1.554373      0   \n",
+       "60         -0.773474  1.283518                     -1.330077 -0.213021      1   \n",
+       "19          0.018129  0.011190                      1.056952  0.312420      0   \n",
+       "114        -0.933525 -0.120430                      0.816836 -1.152447      1   \n",
+       "47          0.450699 -0.208177                      1.014578  0.758249      0   \n",
+       "48          0.493956  0.493797                      0.195361  0.997086      0   \n",
+       "158         3.435432 -1.699872                     -0.920468 -0.276711      2   \n",
+       "133        -0.025128 -0.778531                     -1.866805 -0.467781      2   \n",
+       "137        -0.025128 -0.603037                     -1.301828 -0.738463      2   \n",
+       "154         1.099554 -1.655999                     -1.499570 -0.340401      2   \n",
+       "136        -0.522583 -0.910151                     -1.895054 -0.085641      2   \n",
+       "2           0.269020  0.318304                      0.788587  1.395148      0   \n",
+       "168         1.558078 -0.954024                     -1.146459  0.009893      2   \n",
+       "117        -1.296884  0.449924                      0.491974 -1.279827      1   \n",
+       "32         -0.526909  1.195772                      0.364855  0.774172      0   \n",
+       "22         -0.544212  0.669291                      1.960915  0.917474      0   \n",
+       "108        -1.020039 -0.427544                      0.576721 -1.384915      1   \n",
+       "73         -0.738868  1.546759                      1.254694  0.758249      1   \n",
+       "77         -1.041667  0.011190                     -0.129500 -0.786230      1   \n",
+       "142        -0.306298 -0.295924                     -0.779224 -0.722540      2   \n",
+       "9           0.935177  0.230557                      1.325316  0.949319      0   \n",
+       "85         -1.054644  1.195772                      0.774463 -0.945455      1   \n",
+       "58          0.753498 -0.295924                      0.364855  1.713598      0   \n",
+       "45          0.078689 -0.383670                      1.014578  1.060776      0   \n",
+       "175         2.224236 -1.612125                     -1.485445  0.280575      2   \n",
+       "42          0.160877 -0.339797                      1.339440  1.108544      0   \n",
+       "143        -0.284670 -0.208177                     -0.793348 -0.627005      2   \n",
+       "177         1.791666 -1.524378                     -1.428948 -0.595160      2   \n",
+       "\n",
+       "     predicted_class  \n",
+       "102                1  \n",
+       "84                 1  \n",
+       "96                 2  \n",
+       "65                 0  \n",
+       "79                 1  \n",
+       "17                 0  \n",
+       "109                1  \n",
+       "113                1  \n",
+       "28                 0  \n",
+       "159                2  \n",
+       "38                 0  \n",
+       "34                 0  \n",
+       "125                1  \n",
+       "115                1  \n",
+       "71                 1  \n",
+       "76                 1  \n",
+       "131                2  \n",
+       "33                 0  \n",
+       "60                 1  \n",
+       "19                 0  \n",
+       "114                1  \n",
+       "47                 0  \n",
+       "48                 0  \n",
+       "158                2  \n",
+       "133                2  \n",
+       "137                2  \n",
+       "154                2  \n",
+       "136                2  \n",
+       "2                  0  \n",
+       "168                2  \n",
+       "117                1  \n",
+       "32                 0  \n",
+       "22                 0  \n",
+       "108                1  \n",
+       "73                 0  \n",
+       "77                 1  \n",
+       "142                2  \n",
+       "9                  0  \n",
+       "85                 1  \n",
+       "58                 0  \n",
+       "45                 0  \n",
+       "175                2  \n",
+       "42                 0  \n",
+       "143                2  \n",
+       "177                2  "
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# make predictions on the test set\n",
     "y_pred = knn_final.predict(X_test)\n",
@@ -468,10 +4039,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "2de5a14b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9333333333333333"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# evaluate accuracy_score\n",
     "accuracy_score(y_test, y_pred)\n",