• sklearn模型整理


    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

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  • 原文地址:https://blog.csdn.net/qq_45022743/article/details/125600309