sklearn.base module: Base classes and utility functions
sklearn.calibration module: Probability Calibration(标准、标定)
sklearn.cluster: Clustering
sklearn.cluster.bicluster: Biclustering
sklearn.compose: Composite Estimators
sklearn.covariance: Covariance Estimators（协方差）
sklearn.cross_decomposition: Cross decomposition（交叉分解）
sklearn.datasets: Datasets
sklearn.decomposition: Matrix Decomposition
sklearn.discriminant_analysis: Discriminant Analysis（判别分析）
sklearn.dummy: Dummy estimators
sklearn.ensemble: Ensemble Methods
sklearn.exceptions module(exceptions模块): Exceptions and warnings
sklearn.experimental: Experimental
sklearn.feature_extraction: Feature Extraction
sklearn.feature_selection: Feature Selection
sklearn.gaussian_process: Gaussian Processes
sklearn.isotonic: Isotonic regression
sklearn.impute: Impute
sklearn.kernel_approximation Kernel Approximation
sklearn.kernel_ridge Kernel Ridge Regression
sklearn.linear_model: Generalized Linear Models?
sklearn.manifold: Manifold Learning
sklearn.metrics: Metrics
sklearn.mixture: Gaussian Mixture Models
sklearn.model_selection: Model Selection
sklearn.multiclass: Multiclass and multilabel classification
sklearn.multioutput: Multioutput regression and classification
sklearn.naive_bayes: Naive Bayes
sklearn.neighbors: Nearest Neighbors
sklearn.neural_network: Neural network models
sklearn.pipeline: Pipeline
sklearn.inspection: inspection
sklearn.preprocessing: Preprocessing and Normalization
sklearn.random_projection: Random projection?
sklearn.random_projection: Random projection?
sklearn.svm: Support Vector Machines?
sklearn.tree: Decision Trees?
sklearn.utils: Utilities（实用程序）