原文: http://scikit-learn.org/stable/modules/classes.html
sklearn.base
: Base classes and utility functions:基础类和方法sklearn.cluster
: Clustering:聚集sklearn.cluster.bicluster
: Biclustering:核函数sklearn.covariance
: Covariance Estimators:协方差评估sklearn.model_selection
: Model Selection:模型选择sklearn.datasets
: Datasets:数据集管理sklearn.decomposition
: Matrix Decomposition:矩阵分解sklearn.dummy
: Dummy estimatorssklearn.ensemble
: Ensemble Methods:集成方法(随机森林和gbdt在此)sklearn.exceptions
: Exceptions and warnings 异常和警告sklearn.feature_extraction
: Feature Extraction 特征提取sklearn.feature_selection
: Feature Selection 特征选择sklearn.gaussian_process
: Gaussian Processes 高斯过程sklearn.isotonic
: Isotonic regression 保序回归sklearn.kernel_approximation
Kernel Approximation 内核近似sklearn.kernel_ridge
Kernel Ridge Regression 岭回归sklearn.discriminant_analysis
: Discriminant Analysis 判别分析sklearn.linear_model
: Generalized Linear Models 广义线性模型sklearn.manifold
: Manifold Learningsklearn.metrics
: Metrics 度量(主要各种指标)sklearn.mixture
: Gaussian Mixture Models 高斯混合模型sklearn.multiclass
: Multiclass and multilabel classification 多类和多标记分类sklearn.multioutput
: Multioutput regression and classification 多输出回归和分类sklearn.naive_bayes
: Naive Bayes 朴素贝叶斯sklearn.neighbors
: Nearest Neighbors 最近邻sklearn.neural_network
: Neural network models 神经网络sklearn.calibration
: Probability Calibration 概率校准sklearn.cross_decomposition
: Cross decompositionsklearn.pipeline
: Pipeline 管道sklearn.preprocessing
: Preprocessing and Normalization 预处理和规范化