Copy of mllab8.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Copy of mllab8.ipynb","provenance":[{"file_id":"1y6Pt5pM8QHW5or0ZuMUx48N6HwMxYFiC","timestamp":1573490939080}],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"e5dOc37BmCt3","colab_type":"code","outputId":"1371d036-a46f-46fb-9e9f-8abccc6f02d6","executionInfo":{"status":"ok","timestamp":1573147223041,"user_tz":480,"elapsed":9883,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["import matplotlib.pyplot as plt\n","from sklearn import datasets\n","from sklearn.cluster import KMeans\n","import sklearn.metrics as sm\n","import pandas as pd\n","import numpy as np\n","%matplotlib inline\n","iris = datasets.load_iris()"],"execution_count":0,"outputs":[{"output_type":"stream","text":["{'data': array([[5.1, 3.5, 1.4, 0.2],\n","       [4.9, 3. , 1.4, 0.2],\n","       [4.7, 3.2, 1.3, 0.2],\n","       [4.6, 3.1, 1.5, 0.2],\n","       [5. , 3.6, 1.4, 0.2],\n","       [5.4, 3.9, 1.7, 0.4],\n","       [4.6, 3.4, 1.4, 0.3],\n","       [5. , 3.4, 1.5, 0.2],\n","       [4.4, 2.9, 1.4, 0.2],\n","       [4.9, 3.1, 1.5, 0.1],\n","       [5.4, 3.7, 1.5, 0.2],\n","       [4.8, 3.4, 1.6, 0.2],\n","       [4.8, 3. , 1.4, 0.1],\n","       [4.3, 3. , 1.1, 0.1],\n","       [5.8, 4. , 1.2, 0.2],\n","       [5.7, 4.4, 1.5, 0.4],\n","       [5.4, 3.9, 1.3, 0.4],\n","       [5.1, 3.5, 1.4, 0.3],\n","       [5.7, 3.8, 1.7, 0.3],\n","       [5.1, 3.8, 1.5, 0.3],\n","       [5.4, 3.4, 1.7, 0.2],\n","       [5.1, 3.7, 1.5, 0.4],\n","       [4.6, 3.6, 1. , 0.2],\n","       [5.1, 3.3, 1.7, 0.5],\n","       [4.8, 3.4, 1.9, 0.2],\n","       [5. , 3. , 1.6, 0.2],\n","       [5. , 3.4, 1.6, 0.4],\n","       [5.2, 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5.4, 2.3],\n","       [5.9, 3. , 5.1, 1.8]]), 'target': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n","       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n","       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]), 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='<U10'), 'DESCR': '.. _iris_dataset:\\n\\nIris plants dataset\\n--------------------\\n\\n**Data Set Characteristics:**\\n\\n    :Number of Instances: 150 (50 in each of three classes)\\n    :Number of Attributes: 4 numeric, predictive attributes and the class\\n    :Attribute Information:\\n        - sepal length in cm\\n        - sepal width in cm\\n        - petal length in cm\\n        - petal width in cm\\n        - class:\\n                - Iris-Setosa\\n                - Iris-Versicolour\\n                - Iris-Virginica\\n                \\n    :Summary Statistics:\\n\\n    ============== ==== ==== ======= ===== ====================\\n                    Min  Max   Mean    SD   Class Correlation\\n    ============== ==== ==== ======= ===== ====================\\n    sepal length:   4.3  7.9   5.84   0.83    0.7826\\n    sepal width:    2.0  4.4   3.05   0.43   -0.4194\\n    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\\n    petal width:    0.1  2.5   1.20   0.76    0.9565  (high!)\\n    ============== ==== ==== ======= ===== ====================\\n\\n    :Missing Attribute Values: None\\n    :Class Distribution: 33.3% for each of 3 classes.\\n    :Creator: R.A. Fisher\\n    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\\n    :Date: July, 1988\\n\\nThe famous Iris database, first used by Sir R.A. Fisher. The dataset is taken\\nfrom Fisher\\'s paper. Note that it\\'s the same as in R, but not as in the UCI\\nMachine Learning Repository, which has two wrong data points.\\n\\nThis is perhaps the best known database to be found in the\\npattern recognition literature.  Fisher\\'s paper is a classic in the field and\\nis referenced frequently to this day.  (See Duda & Hart, for example.)  The\\ndata set contains 3 classes of 50 instances each, where each class refers to a\\ntype of iris plant.  One class is linearly separable from the other 2; the\\nlatter are NOT linearly separable from each other.\\n\\n.. topic:: References\\n\\n   - Fisher, R.A. \"The use of multiple measurements in taxonomic problems\"\\n     Annual Eugenics, 7, Part II, 179-188 (1936); also in \"Contributions to\\n     Mathematical Statistics\" (John Wiley, NY, 1950).\\n   - Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.\\n     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\\n   - Dasarathy, B.V. (1980) \"Nosing Around the Neighborhood: A New System\\n     Structure and Classification Rule for Recognition in Partially Exposed\\n     Environments\".  IEEE Transactions on Pattern Analysis and Machine\\n     Intelligence, Vol. PAMI-2, No. 1, 67-71.\\n   - Gates, G.W. (1972) \"The Reduced Nearest Neighbor Rule\".  IEEE Transactions\\n     on Information Theory, May 1972, 431-433.\\n   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al\"s AUTOCLASS II\\n     conceptual clustering system finds 3 classes in the data.\\n   - Many, many more ...', 'feature_names': ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)'], 'filename': '/usr/local/lib/python3.6/dist-packages/sklearn/datasets/data/iris.csv'}\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"5qORcdGPnGmZ","colab_type":"code","outputId":"46935236-3e70-49b3-9ef1-3006f83fce79","executionInfo":{"status":"ok","timestamp":1572960635641,"user_tz":480,"elapsed":1589,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":462}},"source":["X = pd.DataFrame(iris.data)\n","\n","#print(X)\n","X.columns = ['Sepal_Length','Sepal_Width','Petal_Length','Petal_Width']\n","#print(X.columns)\n","#print(\"X:\",x)\n","#print(\"Y:\",y)    \n","y = pd.DataFrame(iris.target)\n","y.columns = ['Targets']\n","\n","# Set the size of the plot\n","plt.figure(figsize=(14,7))\n"," \n","# Create a colormap\n","colormap = np.array(['red', 'lime', 'black'])\n"," \n","# Plot Sepal\n","plt.subplot(1, 2, 1)\n","plt.scatter(X.Sepal_Length,X.Sepal_Width, c=colormap[y.Targets], s=40)\n","plt.title('Sepal')\n","plt.subplot(1, 2, 2)\n","plt.scatter(X.Petal_Length,X.Petal_Width, c=colormap[y.Targets], s=40)\n","plt.title('Petal')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Petal')"]},"metadata":{"tags":[]},"execution_count":29},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAzIAAAGrCAYAAAAbw6KPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n","text/plain":["<Figure size 1008x504 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"rAcqmLRwnje_","colab_type":"code","outputId":"af94eb7f-a63f-44f0-e6b6-b4863b4a9e14","executionInfo":{"status":"ok","timestamp":1572960648937,"user_tz":480,"elapsed":1126,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":146}},"source":["# K Means Cluster\n","model = KMeans(n_clusters=3)\n","model.fit(X)\n","# This is what KMeans thought\n","model.labels_"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 0, 0, 0, 0, 2, 0, 0, 0,\n","       0, 0, 0, 2, 2, 0, 0, 0, 0, 2, 0, 2, 0, 2, 0, 0, 2, 2, 0, 0, 0, 0,\n","       0, 2, 0, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 2], dtype=int32)"]},"metadata":{"tags":[]},"execution_count":30}]},{"cell_type":"code","metadata":{"id":"bNNTePMsocIN","colab_type":"code","outputId":"e9f65e4c-8355-4b47-8040-9027a26fd9d5","executionInfo":{"status":"ok","timestamp":1572960661414,"user_tz":480,"elapsed":1658,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":462}},"source":["# View the results\n","# Set the size of the plot\n","plt.figure(figsize=(14,7))\n"," \n","# Create a colormap\n","colormap = np.array(['red', 'lime', 'black'])\n"," \n","# Plot the Original Classifications\n","plt.subplot(1, 2, 1)\n","plt.scatter(X.Petal_Length, X.Petal_Width, c=colormap[y.Targets], s=40)\n","plt.title('Real Classification')\n"," \n","# Plot the Models Classifications\n","plt.subplot(1, 2, 2)\n","plt.scatter(X.Petal_Length, X.Petal_Width, c=colormap[model.labels_], s=40)\n","plt.title('K Mean Classification')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'K Mean Classification')"]},"metadata":{"tags":[]},"execution_count":31},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAzIAAAGrCAYAAAAbw6KPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdeXhU1f3H8feZmSSzJBMIYRVEkUVR\nUSQuVEQEERdcKBaXqnUBLf7qRoutS60rbtTdVtxQVNxK3VAQbVkUCgrIoha0KAiiAqKQfZvz++MO\nkMlMkkmYZDLh8/KZh8y5557zPePzzJnvvefea6y1iIiIiIiIpBJXsgMQERERERGpLyUyIiIiIiKS\ncpTIiIiIiIhIylEiIyIiIiIiKUeJjIiIiIiIpBwlMiIiIiIiknKUyEjKM8bMMcaMbuC++xhjrDHG\nk+i4wu1fb4x5ssr7EcaY9caYAmNMX2PMZ8aYQY3Q7wxjzG8S3a6IiDQ/xphBxpgNjdj+Y8aYP1d5\nP9YY80N4LmsT/rdbI/TbKHOktBxKZKRJGGPWGmOKw1923xtjnjHGZDZR3z2NMa8aY7YYY7YZY1YY\nY8YZY9yN3be1doK1tmqSNRH4nbU201r7ibX2QGvtnN3pwxhzszHm+Wr9nmStfXZ32hURaSnCc9Dx\nVd6fbYz5yRhzbIy6g8IHuF6rVn5IuHxOE4QcxRhzhDHmHWPMz8aYrcaYj4wxFzVF39ba31prbwvH\nkQbcB5wQnst+DP/71e70Ef5dcHu1fnd7jpSWTYmMNKVTrbWZwKFAX+C6xu7QGLMfsAhYDxxsrc0G\nfgXkAVmN3X8MXYHPktCviIgA4bPVjwKnWGvn1lBtM9DfGNOmStlvgC8aO75YjDH9gX8Dc4HuQBtg\nLHBSEsJpD3jRXCbNgBIZaXLW2u+Bd3ESGgCMMRnGmInGmG/Cp6sfM8b4wttaG2OmG2M2h4+gTTfG\ndI6zu1uABdbacdba78L9r7bWnmut/bl6ZWPMRcaY/xpj8o0xXxljLquyLTfc946jYR8YY1zhbX80\nxnwb3m+1MWZIuPxmY8zz4fEVAG5guTFmTXj7zqOExhh3eCnamnA7S4wxXcLbHgwvSdseLj8mXH4i\ncD1wVvhs1/Jw+c7ldsYYlzHmRmPMOmPMJmPMFGNMdnjbjqV1vwl/9luMMTfE+dmKiKSU8Hf6X4Fh\n1toFtVQtA14Hzg7v5wbOAl6o1t7+xpj3wnPCamPMqCrbTjHGfBL+3l5vjLm5yrb6fvfeCzxrrb3b\nWrvFOpZYa0fFqmyM+VOVueRzY8yIKtu6G2PmhlcobDHGvBwuN8aY+8PzxHZjzEpjzEHhbc8YY243\nxvQEVoeb+tkY8+/wdmuM6R7+22eM+Wt4ztlmjPmwynz+qnFWZWwzxswzxhwYLr8U+DVwbXgueytc\nXnWOzDDGPGCM2Rh+PWCMyQhvG2SM2WCM+X04/u9ME52tkuRSIiNNLpyEnAT8r0rxXUBPnOSmO7AX\ncFN4mwuYjHM2Y2+gGHgkzu6OB/5Rj/A2AcOBIHARcL8x5rDwtt8DG4C2OEekrgesMaYX8DvgcGtt\nFjAMWFu1UWttafhsFMAh1tr9YvQ9DjgHODnc/8VAUXjbxzifTQ4wFXjVGOO11s4EJgAvh0/tHxKj\n3QvDr+OAbkAm0Z/fAKAXMAS4yRhzQA2fj4hIqhoL3AoMsdYujqP+FOCC8N/DgE+BjTs2GmMCwHs4\n38ntcJKevxljeoerFIb3bwWcAow1xpxRrY86v3uNMX6gP/Wby9YAxwDZOAf0njfGdAxvuw2YBbQG\nOgMPh8tPAAbizMXZwCjgx6qNWmu/AA4Mv21lrR0co++JQD/gFzhz1rVAKLxtBtAD5/NaSjgxtNY+\nHv77nvBcdmqMdm8AjsKZCw8BjgBurLK9QzjuvYBLgEeNMa1jfjrSYiiRkab0ujEmH2eZ1ybgL+Ac\nBQIuBa6x1m611ubj/Dg/GyC8/naatbYovO0OIGpdcw3aAN/FG6C19m1r7Zrw0a65OF/2x4Q3lwMd\nga7W2nJr7QfWWgtUAhlAb2NMmrV2rbV2Tbx9VjEauDF8xshaa5dba38Mx/V8+HOosNb+Ndxfrzjb\n/TVwn7X2K2ttAc6SvrNN5A0ObrHWFltrlwPLcSYJEZGWZCiwEFgZT+XwGZuc8MGqC3ASm6qGA2ut\ntZPD382fANNwli9jrZ1jrV1prQ1Za1cALxI9d8Xz3dsa5/dafeayV621G8N9vwx8ifPDH5y5rCvQ\nyVpbYq39sEp5FrA/YKy1/92xkiFexlmlcDFwlbX2W2ttpbV2gbW2NBzX09ba/PD7m4FDdqwQiMOv\ngVuttZustZtxErTzq2wvD28vt9a+AxQQ/zwpKUqJjDSlM8JnLAbhfFHmhsvbAn5giXGWbf0MzAyX\nY4zxG2MmhU9TbwfmAa1MfBfr/4iTfMTFGHOSMWZheJnAzzhnR3bEeS/OWaRZxll29icAa+3/gKtx\nvpQ3GWNeMsZ0irfPKrrgHEWLFdcfjLPkbVs4ruwqcdWlE7Cuyvt1gAfnrNIO31f5uwjnrI2ISEsy\nFudsw5PhA2jxeA7njPtxwGvVtnUFjtwxb4W/m3+Nc2YAY8yRxpjZxlkWvQ34LdHf2/F89/6Ec0aj\nPnPZBcaYZVXiOqhK39cCBvjIOHcFuxjAWvtvnLP1j+LMZY8bY4Lx9hmWi3P9TNRcZpzl03eFl7xt\nZ9fKhd2Zy6rOtT9aayuqvNdctgdQIiNNLnym4xmc088AW3CWix1orW0VfmVXWYr1e5yjKkdaa4M4\np77B+SKuy/vAyHjiCq+1nRaOq721thXwzo5+wkeRfm+t7QacBowz4WthrLVTrbUDcCY2C9wdT5/V\nrAeilpwZ53qYa3FO87cOx7WNXeO3dbS7MRzXDnsDFcAPDYhRRCRV/YCzhOsY4G9x7vMccDnwjrW2\nqNq29cDcKvNWq/CyqLHh7VOBN4Eu4RvNPEZ881aEcL//If65rCvwBE4C1iY8Z3zKrrnse2vtGGtt\nJ+AynOVw3cPbHrLW9gN64yR94+sZ7haghBhzGXAucDrOku9sYJ8dIYf/bchctrGGurKHUCIjyfIA\nMNQYc4i1NoTzpXu/MaYdgDFmL2PMsHDdLJxE52djTA7hJWlx+gvwC2PMvcaYHUfJuhvnAvxW1eqm\n4yzZ2gxUGGNOwlkzTHi/4eF9DU4iUQmEjDG9jDGDw4lQSTjWEPX3JHCbMaaHc82l6WOcO+Zk4SQe\nmwGPMeYmnGtodvgB2Cd8Sj+WF4FrjDH7GueW1zuuqamoob6ISItkrd2Ik8ycaIy5P476X+MsB4t1\nIf50oKcx5nxjTFr4dXiV61yygK3W2hJjzBE4P+Qb6lrgQmPM+PC8sON20C/FqBvASQo2h+tdhHNG\nhvD7X5ldN8z5KVw3FI79SOPcXrkQZz6r11wWns+fBu4zxnQKn4XpH54fs4BSnJUSfpy5qKofcK7j\nrMmLwI3GmLbGmFyc62ifr6W+7AGUyEhShNe3TmHXBf1/xFm2tTB8yvl9dq1tfQDw4RzpWYiz7Cze\nftbgXCS5D/BZ+PT+NGAxkF+tbj5wJfAKzpf7uThH03boEY6rAOfo2N+stbNxkp+7wvF9j3MRY0Nu\nLX1fuO9ZwHbgKZxxv4sz5i9wTqWX4BwJ3OHV8L8/GmOWxmj3aZyjivOAr8P7X9GA+EREUp619htg\nMHCmMebOOOp/GE6Aqpfn4xzsOhvnzMD3OGfjM8JVLgduDV8behPO93tDY14Qjnkw8JUxZivwOM6q\ngep1P8e5M9t/cJKDg4H5VaocDiwyzp0038S5nuUrnANkT+DMf+twEo57GxDuH3CuQ/oY2Irzmbhw\n5vx1wLfA5zjzeVVP4Vxr+rMx5vUY7d6OM3evCLe/NFwmezDjXKssIiIiIiKSOnRGRkREREREUo4S\nGRERERERSTlKZEREREREJOUokRERERERkZTjqbtK48jNzbX77LNPsroXERFgyZIlW6y1bZMdR3Ok\neUpEJPlqm6eSlsjss88+LF68OFndi4gIYIxZV3etPZPmKRGR5KttntLSMhERERERSTlKZERERERE\nJOUokRERERERkZSjREZERERERFKOEhkREREREUk5SmRERERERCTlKJEREREREZGUo0RGRERERERS\njhIZERERERFJOUpkREREREQk5SiRERERERGRlKNERkREREREUo4SGRERERERSTlKZEQkZVRUVDBx\n4kS6detG27ZtOeuss/jyyy/r1cbcuXMZOHAgbdq0oW/fvvzzn/9k27ZtjB8/nk6dOtGhQweuvPJK\nfvzxx0YahYiItFjWwpNPwgEHQJs2cMop8Mkn9Wtj6VI4+WRn/wMOgKeeguJiuO022HtvaNsWLroI\n1q9vnDGkEGOtrb2CMV2AKUB7wAKPW2sfrFZnEPAG8HW46J/W2ltrazcvL88uXry4gWGLyJ7o9NNP\n5/3336eoqAgAl8tFZmYmS5cuZb/99qtz/7feeouzzz575/4APp+PrKwstm3bRmlpKQDp6el06tSJ\nFStWkJWV1TiDaSaMMUustXnJjmN3aJ4SkWbjiivg6adhxzxjDPh8MHs2HHFE3fsvWgSDB+/aH5z9\nW7eGn35yEhoAtxtatYKVK6Fjx8SPoxmpbZ6K54xMBfB7a21v4Cjg/4wxvWPU+8Bae2j4VevkICJS\nX0uXLo1IYgBCoRAFBQX85S9/qXN/ay1XXHFFxP4AxcXFbNq0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94oKZ0laHHMa5eVO23HM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\nw3GQkSRJkjQcBxlJkiRJw/kNcceM84mzPhIAAAAASUVORK5CYII=\n","text/plain":["<Figure size 1008x504 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"Y3cGt_gfqtrT","colab_type":"code","outputId":"5908b897-2c91-41e5-f5c0-75f65ba3ba9e","executionInfo":{"status":"ok","timestamp":1572960684829,"user_tz":480,"elapsed":897,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":109}},"source":["# The fix, we convert all the 1s to 0s and 0s to 1s.\n","predY = np.choose(model.labels_, [0, 1, 2]).astype(np.int64)\n","print (predY)"],"execution_count":0,"outputs":[{"output_type":"stream","text":["[1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n"," 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n"," 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 0 0 0 0 2 0 0 0 0\n"," 0 0 2 2 0 0 0 0 2 0 2 0 2 0 0 2 2 0 0 0 0 0 2 0 0 0 0 2 0 0 0 2 0 0 0 2 0\n"," 0 2]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0fGoZFvxq-C2","colab_type":"code","outputId":"9afc0166-7d0d-4b5c-914e-65e44a8b2adf","executionInfo":{"status":"ok","timestamp":1572960744483,"user_tz":480,"elapsed":1603,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":462}},"source":["plt.figure(figsize=(14,7))\n"," \n","# Create a colormap\n","colormap = np.array(['red', 'lime', 'black'])\n"," \n","# Plot Orginal\n","plt.subplot(1, 2, 1)\n","plt.scatter(X.Petal_Length, X.Petal_Width, c=colormap[y.Targets], s=40)\n","plt.title('Real Classification')\n"," \n","# Plot Predicted with corrected values\n","plt.subplot(1, 2, 2)\n","plt.scatter(X.Petal_Length,X.Petal_Width, c=colormap[predY], s=40)\n","plt.title('K Mean Classification')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'K Mean Classification')"]},"metadata":{"tags":[]},"execution_count":33},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAzIAAAGrCAYAAAAbw6KPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nX0uXLo1IYgBCoRAFBQX85S9/qXN/ay1XXHFFxP4AxcXFbNq0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94oKZ0laHHMa5eVO23HM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\nw3GQkSRJkjQcBxlJkiRJw/kNcceM84mzPhIAAAAASUVORK5CYII=\n","text/plain":["<Figure size 1008x504 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"rT92DuY8rREM","colab_type":"code","outputId":"452f40bb-7fdc-4c2c-ad30-7eb4ca76bafe","executionInfo":{"status":"ok","timestamp":1572960754363,"user_tz":480,"elapsed":889,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":35}},"source":["sm.accuracy_score(y, model.labels_)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.09333333333333334"]},"metadata":{"tags":[]},"execution_count":34}]},{"cell_type":"code","metadata":{"id":"10tXDsBur_IK","colab_type":"code","outputId":"5099c1ca-4b2e-45b3-8d62-472e28d32720","executionInfo":{"status":"ok","timestamp":1572960771946,"user_tz":480,"elapsed":1096,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":72}},"source":["# Confusion Matrix\n","sm.confusion_matrix(y, model.labels_)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 0, 50,  0],\n","       [ 2,  0, 48],\n","       [36,  0, 14]])"]},"metadata":{"tags":[]},"execution_count":35}]},{"cell_type":"code","metadata":{"id":"lX0CzU7Mttf9","colab_type":"code","outputId":"8b0d650e-522d-4b81-cffb-a5e30338de56","executionInfo":{"status":"ok","timestamp":1572960774978,"user_tz":480,"elapsed":1097,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":206}},"source":["from sklearn import preprocessing\n","\n","scaler = preprocessing.StandardScaler()\n","\n","scaler.fit(X)\n","xsa = scaler.transform(X)\n","xs = pd.DataFrame(xsa, columns = X.columns)\n","xs.sample(5)"],"execution_count":0,"outputs":[{"output_type":"execute_result","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>Sepal_Length</th>\n","      <th>Sepal_Width</th>\n","      <th>Petal_Length</th>\n","      <th>Petal_Width</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>31</th>\n","      <td>-0.537178</td>\n","      <td>0.788808</td>\n","      <td>-1.283389</td>\n","      <td>-1.052180</td>\n","    </tr>\n","    <tr>\n","      <th>126</th>\n","      <td>0.432165</td>\n","      <td>-0.592373</td>\n","      <td>0.592246</td>\n","      <td>0.790671</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>-1.870024</td>\n","      <td>-0.131979</td>\n","      <td>-1.510739</td>\n","      <td>-1.447076</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>-1.021849</td>\n","      <td>0.788808</td>\n","      <td>-1.283389</td>\n","      <td>-1.315444</td>\n","    </tr>\n","    <tr>\n","      <th>74</th>\n","      <td>0.674501</td>\n","      <td>-0.362176</td>\n","      <td>0.308059</td>\n","      <td>0.132510</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["     Sepal_Length  Sepal_Width  Petal_Length  Petal_Width\n","31      -0.537178     0.788808     -1.283389    -1.052180\n","126      0.432165    -0.592373      0.592246     0.790671\n","13      -1.870024    -0.131979     -1.510739    -1.447076\n","7       -1.021849     0.788808     -1.283389    -1.315444\n","74       0.674501    -0.362176      0.308059     0.132510"]},"metadata":{"tags":[]},"execution_count":36}]},{"cell_type":"code","metadata":{"id":"W3NtT7tPunXO","colab_type":"code","outputId":"e5b397b2-86f0-47e2-c179-0b6b7733907a","executionInfo":{"status":"ok","timestamp":1572960783272,"user_tz":480,"elapsed":846,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":90}},"source":["from sklearn.mixture import GaussianMixture\n","gmm = GaussianMixture(n_components=3)\n","gmm.fit(xs)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["GaussianMixture(covariance_type='full', init_params='kmeans', max_iter=100,\n","                means_init=None, n_components=3, n_init=1, precisions_init=None,\n","                random_state=None, reg_covar=1e-06, tol=0.001, verbose=0,\n","                verbose_interval=10, warm_start=False, weights_init=None)"]},"metadata":{"tags":[]},"execution_count":37}]},{"cell_type":"code","metadata":{"id":"DxU02uSWvidq","colab_type":"code","outputId":"4129a0cf-68f3-4953-9ec3-1a96a708ec8a","executionInfo":{"status":"ok","timestamp":1572960788331,"user_tz":480,"elapsed":2455,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":146}},"source":["y_cluster_gmm = gmm.predict(xs)\n","y_cluster_gmm"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n","       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n","       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"]},"metadata":{"tags":[]},"execution_count":38}]},{"cell_type":"code","metadata":{"id":"1pQfrxsGvnXc","colab_type":"code","outputId":"1d0a62e3-1ab3-46f8-e7bf-f42980b5eaf9","executionInfo":{"status":"ok","timestamp":1572960791321,"user_tz":480,"elapsed":1041,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":299}},"source":["plt.subplot(1, 2, 1)\n","plt.scatter(X.Petal_Length, X.Petal_Width, c=colormap[y_cluster_gmm], s=40)\n","plt.title('GMM Classification')"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'GMM Classification')"]},"metadata":{"tags":[]},"execution_count":39},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAL0AAAEICAYAAAAKp/VCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQ2+6T990KS4uliFDhlT59J1OpzgcDnG5XOJyuUQpJW63W3r3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EM8deY47j92JX/kZmTGS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\npZQ6EQAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"eIHHrtnGv8EW","colab_type":"code","outputId":"867c8921-5f4b-485e-d1a9-ae290ec4c527","executionInfo":{"status":"ok","timestamp":1572960794484,"user_tz":480,"elapsed":906,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":35}},"source":["sm.accuracy_score(y, y_cluster_gmm)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.9666666666666667"]},"metadata":{"tags":[]},"execution_count":40}]},{"cell_type":"code","metadata":{"id":"ibYMmrRKwG4m","colab_type":"code","outputId":"39a5bcf1-f344-442d-e968-3e26955acf1e","executionInfo":{"status":"ok","timestamp":1572960807079,"user_tz":480,"elapsed":963,"user":{"displayName":"Shetty Sonali","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDS-wXPWz3krvBrC-06FoXxyOofD55c7KXoAqX6=s64","userId":"12958854954382670203"}},"colab":{"base_uri":"https://localhost:8080/","height":72}},"source":["sm.confusion_matrix(y, y_cluster_gmm)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[50,  0,  0],\n","       [ 0, 45,  5],\n","       [ 0,  0, 50]])"]},"metadata":{"tags":[]},"execution_count":41}]},{"cell_type":"code","metadata":{"id":"lYqa3JuQwSxa","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}