OpenML

sklearn.linear_model.base.LinearRegression (3)

Ordinary least squares Linear Regression.

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sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (7)

Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…

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__main__.DecisionStumpClassifier (1)

Decision Stump classifier supports native nominal features

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__main__.DecisionStumpClassifierV2 (1)

Decision Stump classifier V2 supports native nominal features

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sklearn.pipeline.Pipeline(tranformer=sklearn.compose._column_transformer.ColumnTransformer(one_hot_encoder=sklearn.preprocessing._encoders.OneHotEncoder),scaler=sklearn.preprocessing._data.StandardScaler,classifier=sklearn.linear_model._logistic.LogisticRegression) (1)

Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…

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sklearn.ensemble._forest.RandomForestClassifier (1)

A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive…

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sklearn.linear_model._logistic.LogisticRegression (2)

Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the 'multi_class' option is set to 'ovr', and uses the…

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sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier) (2)

Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…

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torch.nn.modules.container.Sequential.463f77fdacfeba1b (1)

Automatically created pytorch flow.

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torch.nn.modules.container.Sequential.a33ac9039500e765 (1)

Automatically created pytorch flow.

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torch.nn.modules.container.Sequential.77d43b3180263d56 (1)

Automatically created pytorch flow.

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torch.nn.modules.container.Sequential.9171040a49232214 (1)

Automatically created pytorch flow.

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sklearn.svm._classes.SVC (2)

C-Support Vector Classification. The implementation is based on libsvm. The fit time scales at least quadratically with the number of samples and may be impractical beyond tens of thousands of…

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sklearn.pipeline.Pipeline(step1=sklearn.impute._base.SimpleImputer,step2=sklearn.svm._classes.SVC) (1)

Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…

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torch.nn.modules.container.Sequential.bdbb959781617ffd (1)

Automatically created pytorch flow.

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sklearn.linear_model._base.LinearRegression (1)

Ordinary least squares Linear Regression. LinearRegression fits a linear model with coefficients w = (w1, ..., wp) to minimize the residual sum of squares between the observed targets in the dataset,…

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sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC)) (1)

Probability calibration with isotonic regression or sigmoid. See glossary entry for :term:`cross-validation estimator`. With this class, the base_estimator is fit on the train set of the…

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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC) (1)

Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…

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torch.nn.modules.container.Sequential.e661c6d4bfeb5869 (1)

Automatically created pytorch flow.

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torch.nn.modules.container.Sequential.5072c546822f7c72 (1)

Automatically created pytorch flow.

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mxnet.gluon.nn.basic_layers.HybridSequential.3eebcc0b (2)

Automatically created MXNet flow.

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mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2 (2)

Automatically created MXNet flow.

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mxnet.gluon.nn.basic_layers.HybridSequential.8150bebd (1)

Automatically created MXNet flow.

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mxnet.gluon.nn.basic_layers.HybridSequential.1b542efd (1)

Automatically created MXNet flow.

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onnx.onnx_pb2.ModelProto.f1b556b3 (1)

Automatically created ONNX flow.

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sklearn.svm._classes.SVC (4)

C-Support Vector Classification. The implementation is based on libsvm. The fit time scales at least quadratically with the number of samples and may be impractical beyond tens of thousands of…

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Automatically created scikit-learn flow.

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sklearn.pipeline.C3766ba67c576ba(n18=sklearn.pipeline.C3766ba67c5714c(n19=sklearn.pipeline.C3766ba67c55d0b(n20=sklearn.compose._column_transformer.C58a45d72d553b(n21=sklearn.preprocessing._function_transformer.C58a45d72d54e6),n22=fastsklearnfeature.transformations.MinMaxScalingTransformation.C3766ba67c5597e),n23=sklearn.pipeline.C3766ba67c56d68(n24=sklearn.compose._column_transformer.C3766ba67c569db(n25=sklearn.preprocessing._function_transformer.C58a45d72d5740),n26=fastsklearnfeature.transformations.OneDivisionTransformation.C58a45d72d579a)),n27=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766ba67c57555,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a4609626de7(n28=sklearn.pipeline.C58a4609626d53(n29=sklearn.pipeline.C58a4609626ba0(n30=sklearn.compose._column_transformer.C3766bc5dd82dad(n31=sklearn.preprocessing._function_transformer.C3766bc5dd82afa),n32=fastsklearnfeature.transformations.MinMaxScalingTransformation.C3766bc5dd83146),n33=sklearn.pipeline.C58a4609626cf6(n34=sklearn.compose._column_transformer.C3766bc5dd83e0d(n35=sklearn.preprocessing._function_transformer.C3766bc5dd83cbf),n36=fastsklearnfeature.transformations.OneDivisionTransformation.C3766bc5dd84009)),n37=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766bc5dd84986,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a46530638f9(n1=sklearn.compose._column_transformer.C3766bf3e3e33da(n2=sklearn.preprocessing._function_transformer.C3766bf3e3e3080),c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C3766bf427d80a9(n3=sklearn.pipeline.C3766bf427d7bb0(n4=sklearn.pipeline.C3766bf427d6edd(n5=sklearn.compose._column_transformer.C58a465372f13c(n6=sklearn.preprocessing._function_transformer.C3766bf427d6a43)),n7=sklearn.pipeline.C3766bf427d78ef(n8=sklearn.compose._column_transformer.C3766bf427d7773(n9=sklearn.preprocessing._function_transformer.C58a465372f237))),n10=fastsklearnfeature.transformations.IdentityTransformation.C3766bf427d7f8b,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a467e987050(n1=sklearn.compose._column_transformer.C3766c0f1f46021(n2=sklearn.preprocessing._function_transformer.C3766c0f1f45bf3),c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a467f4ecaed(n3=sklearn.pipeline.C3766c0f913e7b3(n4=sklearn.pipeline.C3766c0f913d9e1(n5=sklearn.compose._column_transformer.C58a467f4ec8b8(n6=sklearn.preprocessing._function_transformer.C3766c0f913d4ef)),n7=sklearn.pipeline.C58a467f4eca09(n8=sklearn.compose._column_transformer.C58a467f4ec9da(n9=sklearn.preprocessing._function_transformer.C3766c0f913e15b))),n10=fastsklearnfeature.transformations.IdentityTransformation.C3766c0f913ebaf,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C3766c141d85411(n11=sklearn.pipeline.C3766c141d84eaa(n12=sklearn.pipeline.C3766c141d83ff8(n13=sklearn.compose._column_transformer.C58a4686959f5e(n14=sklearn.preprocessing._function_transformer.C3766c141d83700),n15=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C3766c141d83d23),n16=sklearn.pipeline.C58a468695a11e(n17=sklearn.compose._column_transformer.C3766c141d84990(n18=sklearn.preprocessing._function_transformer.C58a468695a0d3))),n19=fastsklearnfeature.transformations.IdentityTransformation.C3766c141d852b7,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a4691b2b6ea(n20=sklearn.pipeline.C3766c1b0fb1b84(n21=sklearn.pipeline.C58a4691b2b475(n22=sklearn.compose._column_transformer.C3766c1b0fb0956(n23=sklearn.preprocessing._function_transformer.C3766c1b0fb0692)),n24=sklearn.pipeline.C3766c1b0fb17f3(n25=sklearn.compose._column_transformer.C3766c1b0fb163f(n26=sklearn.preprocessing._function_transformer.C58a4691b2b54b))),n27=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766c1b0fb20f2,n28=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C58a4691b2b6b9,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C3767670fabb78b(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C376767b31c5274(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a575b4d2fb5(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C37676ae5b25b9d(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a5793d24066(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C37676bd9d1f8a3(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C37676bea30dab3(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a57987b7447(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C37676c0fa6a5e3(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C37676c36da5590(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a579ff6778b(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing._encoders.OneHotEncoder,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a57c601a9c1(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C37676eb8c1b457(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C37676f07fa7aa7(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C376770cb31af78(n1=sklearn.compose._column_transformer.C58a581451c46b(n2=sklearn.preprocessing._function_transformer.C58a581451c414),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C58a5829714fa0(n3=sklearn.pipeline.C3767719e6d16a5(n4=sklearn.pipeline.C3767719e6d0937(n5=sklearn.compose._column_transformer.C58a5829714d78(n6=sklearn.preprocessing._function_transformer.C3767719e6d045a)),n7=sklearn.pipeline.C3767719e6d13a0(n8=sklearn.compose._column_transformer.C3767719e6d1234(n9=sklearn.preprocessing._function_transformer.C58a5829714e80))),n10=fastsklearnfeature.transformations.IdentityTransformation.C3767719e6d1ad1,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C376771ff9d5230(n1=sklearn.impute.SimpleImputer,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C58a5cba134322(n1=sklearn.pipeline.C37679f44c099a3(n2=sklearn.pipeline.C37679f44c090a7(n3=sklearn.compose._column_transformer.C37679f44c08dae(n4=sklearn.preprocessing._function_transformer.C37679f44c08c2e),n5=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C37679f44c08f90),n6=sklearn.pipeline.C37679f44c09759(n7=sklearn.compose._column_transformer.C37679f44c0951d(n8=sklearn.preprocessing._function_transformer.C58a5cba134208),n9=fastsklearnfeature.transformations.ImputationTransformation.C37679f44c0966f)),n10=fastsklearnfeature.transformations.IdentityTransformation.C58a5cba13430d,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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torch.nn.modules.container.Sequential.e88dfaf8998b5af (1)

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sklearn.pipeline.C37685d5183c8ca(n1=sklearn.compose._column_transformer.C37685d5183c6d3(n2=sklearn.preprocessing._function_transformer.C58a6fbb59fa15),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C58a6fc7b9a564(n1=sklearn.compose._column_transformer.C37685dcd406d2a(n2=sklearn.preprocessing._function_transformer.C37685dcd406840),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C37685dd9577d42(n3=sklearn.compose._column_transformer.C37685dd9576900(n4=sklearn.preprocessing._function_transformer.C58a6fc8ef237f),n5=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C58a6fc8ef257c,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C58a6fe15698cd(n6=sklearn.pipeline.C8dd7fcef0f2f(n7=sklearn.pipeline.C37685ecd61db3f(n8=sklearn.compose._column_transformer.C58a6fe1569570(n9=sklearn.preprocessing._function_transformer.C37685ecd61d389)),n10=sklearn.pipeline.C37685ecd61e944(n11=sklearn.compose._column_transformer.C37685ecd61e652(n12=sklearn.preprocessing._function_transformer.C37685ecd61e46e))),n13=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C37685ecd61f5e2,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C376860efbc5e52(n1=sklearn.compose._column_transformer.C376860efbc56e6(n2=sklearn.preprocessing._function_transformer.C376860efbc4fbf),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C37686126d86b3c(n3=sklearn.compose._column_transformer.C58a701d7c09f2(n4=sklearn.preprocessing._function_transformer.C37686126d86014),n5=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C37686126d8680b,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C3768649f29d130(n14=sklearn.pipeline.C3768649f29cae7(n15=sklearn.pipeline.C3768649f29b836(n16=sklearn.compose._column_transformer.C3768649f29b177(n17=sklearn.preprocessing._function_transformer.C58a707650f7e5),n18=fastsklearnfeature.transformations.PandasDiscretizerTransformation.C8dd80bd4e5a9),n19=sklearn.pipeline.C3768649f29c71f(n20=sklearn.compose._column_transformer.C58a707650f9c9(n21=sklearn.preprocessing._function_transformer.C3768649f29bfd4),n22=fastsklearnfeature.transformations.ImputationTransformation.C3768649f29c566)),n23=fastsklearnfeature.transformations.IdentityTransformation.C3768649f29cffa,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.tree.tree.DecisionTreeClassifier (41)

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sklearn.pipeline.Pipeline(polynomialfeatures=sklearn.preprocessing.data.PolynomialFeatures,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.StandardScaler,lr=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C3768b843a7597a(n1=sklearn.compose._column_transformer.C3768b843a7510a(n2=sklearn.preprocessing._function_transformer.C8dd8e1f4df75),c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C58a78d3e4c058(n3=sklearn.compose._column_transformer.C58a78d3e4bfe7(n4=sklearn.preprocessing._function_transformer.C58a78d3e4bfb3),n5=fastsklearnfeature.transformations.OneDivisionTransformation.C3768b846ef81b5,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C3768b852024a15(n6=sklearn.compose._column_transformer.C3768b8520243dd(n7=sklearn.preprocessing._function_transformer.C3768b8520240f3),n8=fastsklearnfeature.transformations.OneDivisionTransformation.C3768b85202476c,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C3768b867c37357(n9=sklearn.pipeline.C3768b867c36a79(n10=sklearn.pipeline.C3768b867c35aca(n11=sklearn.compose._column_transformer.C3768b867c3575f(n12=sklearn.preprocessing._function_transformer.C58a78d72d2216)),n13=sklearn.pipeline.C3768b867c3673d(n14=sklearn.compose._column_transformer.C3768b867c36565(n15=sklearn.preprocessing._function_transformer.C3768b867c363d7))),n16=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3768b867c36eef,n17=fastsklearnfeature.transformations.OneDivisionTransformation.C3768b867c37181,c=sklearn.linear_model.logistic.LogisticRegression) (1)

Automatically created scikit-learn flow.

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sklearn.pipeline.C3768b8d8a65246(n18=sklearn.pipeline.C3768b8d8a64b4a(n19=sklearn.pipeline.Ce2f49f1d489(n20=sklearn.compose._column_transformer.C3768b8d8a6309b(n21=sklearn.preprocessing._function_transformer.C3768b8d8a62da5),n22=fastsklearnfeature.transformations.OneDivisionTransformation.C58a78e277053d),n23=sklearn.pipeline.C3768b8d8a64714(n24=sklearn.compose._column_transformer.C3768b8d8a641b7(n25=sklearn.preprocessing._function_transformer.C3768b8d8a6404f),n26=fastsklearnfeature.transformations.MinMaxScalingTransformation.C3768b8d8a644e4)),n27=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3768b8d8a65088,c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C3768c29dfb5eca(n1=sklearn.compose._column_transformer.C3768c29dfb5c95(n2=sklearn.preprocessing._function_transformer.C3768c29dfb5a6e),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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sklearn.pipeline.C3768c2e8b897cb(n1=sklearn.compose._column_transformer.C3768c2e8b88ef9(n2=sklearn.preprocessing._function_transformer.C58a79e4127410),c=sklearn.linear_model.logistic.LogisticRegression) (1)

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