sklearn.linear_model:Linear Models
Linear classifiers
- linear_model.logisticRegression()
- linear_model.logisticRegressionCV()
- linear_model.PassiveAggressiveClassifier()
- linear_model.Perceptron()
- linear_model.RidgeClassifier()
- linear_model.RidgeClassifierCV()
- linear_model.SGDClassifier()
- linear_model.SGDOneClassSVM()
Classical linear regressors
- linear_model.LinearRegression()
- linear_model.Ridge()
- linear_model.RidgeCV()
- linear_model.SGDRegressor()
Regressors with variable selection
- linear_model.ElasticNet()
- linear_model.ElasticNetCV()
- linear_model.Lars()
- linear_model.LarsCV()
- linear_model.Lasso()
- linear_model.LassoCV()
- linear_model.LassoLars()
- linear_model.LassoLarsCV()
- linear_model.LassoLarsIC()
- linear_model.linear_model.OrthogonalMatchingPursuit()
- linear_model.OrthogonalMatchingPursuitCV()
Bayesian regressors
- linear_model.ARDRegression()
- linear_model.BayesianRidge()
Multi-task linear regressors with variable selection
- linear_model.MultiTaskElasticNet()
- linear_model.MultiTaskElasticNetCV()
- linear_model.MultiTaskLasso()
- linear_model.MultiTaskLassoCV()
Outlier-robust regressors
- linear_model.HuberRegressor()
- linear_model.QuantileRegressor()
- linear_model.RANSACRegressor()
- linear_model.TheilSenRegressor()
Outlier-robust regressors
- linear_model.PoissonRegerssor()
- linear_model.TweedieRegerssor()
- linear_model.GammaRegerssor()
Outlier-robust regressors
- linear_model.PassiveAggressiveRegressor()
- linear_model.enet_path()
- linear_model.lars_path()
- linear_model.lars_path_gram()
- linear_model.lasso_path()
- linear_model.orthogonal_mp()
- linear_model.orthogonal_mp_gram()
- linear_model.ridge_regression()
sklearn.gaussian_process:Gaussian Processes
- gaussian_process.GaussianProcessesClassifier()
- gaussian_process.GaussianProcessesRegressor()
sklearn.neighbors: Nearest Neighbors
- neighbors.KNeighborsClassifier()
- neighbors.KNeighborsr()
- neighbors.RadiusNeighborsClassifier()
- neighbors.RadiusNeighborsRegressor()
sklearn.neural_network: Neural network models
- neural_network.BernoulliRBM()
- neural_network.MLPClassifier()
- neural_network.MLPRegressor()
sklearn.svm: Support Vector Machines
- svm.LinearSVC()
- svm.LinearSVR()
- svm.NuSVC()
- svm.NuSVR()
- svm.OneClassSVM()
- svm.SVC()
- svm.SVR()
sklearn.tree: Decision Trees
- tree.DecisionTreeClassifier()
- tree.DecisionRegressor()
- tree.ExtraTreeClassifier()
- tree.ExtraTreeRegressor()
- tree.export_graphviz()
sklearn.naive_bayes: Naive Bayes
- naive_bayes.BernoulliNB()
- naive_bayes.CategoricalNB()
- naive_bayes.ComplementNB()
- naive_bayes.GaussianNB()
- naive_bayes.MultinomialNB()
sklearn.ensemble: Ensemble Methods
- ensemble.AdaBoostClassifier()
- ensemble.AdaBoostRegressor()
- ensemble.BaggingClassifier()
- ensemble.BaggingRegressor()
- ensemble.ExtraTreesClassifier()
- ensemble.ExtraTreesRegressor()
- ensemble.GradientBoostingClassifier()
- ensemble.GradientBoostingRegressor()
- ensemble.IsolationForest()
- ensemble.RandomForestClassifier()
- ensemble.RandomForestRegressor()
- ensemble.RandomTreesEmbedding()
- ensemble.StackingClassifier()
- ensemble.StackingRegressor()
- ensemble.VotingClassifier()
- ensemble.VotingRegressor()
- ensemble.HistGradientBoostingRegressor()
- ensemble.HistGradientBoostingClassifier()
除此之外,还有lgbm,xgboost,catboosting
参考:sklearn官网