Summary 機器學習：使用Python 簡介Scikit-learn 機器學習 分類法 Classification Ex 1: Recognizing hand-written digits EX 2: Normal and Shrinkage Linear Discriminant Analysis for classification EX 3: Plot classification probability EX 4: Classifier Comparison EX 5: Linear and Quadratic Discriminant Analysis with confidence ellipsoid 特徵選擇 Feature Selection Ex 1: Pipeline Anova SVM Ex 2: Recursive Feature Elimination Ex 3: Recursive Feature Elimination with Cross-Validation Ex 4: Feature Selection using SelectFromModel Ex 5: Test with permutations the significance of a classification score Ex 6: Univariate Feature Selection 互分解 Cross Decomposition 通用範例 General Examples Ex 1: Plotting Cross-Validated Predictions Ex 2: Concatenating multiple feature extraction methods Ex 3: Isotonic Regression Ex 4: Imputing missing values before building an estimator Ex 7: Face completion with a multi-output estimators 群聚法 Clustering EX 12:Spectral clustering for image segmentation 機器學習資料集 Datasets Ex 1: The digits 手寫數字辨識 Ex 3: The iris 鳶尾花資料集 應用範例 Application 波士頓房地產雲端評估(一) 波士頓房地產雲端評估(二)