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Andreas Mueller
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Andreas's flows

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),logisticregression=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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (31)
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(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(anothersimpleimputer=__main__.AnotherSimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (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…
42 runs0 likes0 downloads0 reach0 impact
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(anothersimpleimputer=__main__.AnotherSimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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sklearn.pipeline.Pipeline(anothersimpleimputer=__main__.AnotherSimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder) (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…
0 runs0 likes0 downloads0 reach0 impact
__main__.AnotherSimpleImputer (1)
Clone of SimpleImputer to circumvent OpenML restriction
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sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (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…
20 runs0 likes0 downloads0 reach0 impact
sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder) (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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (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…
92 runs0 likes1 downloads1 reach0 impact
sklearn.compose._column_transformer.ColumnTransformer(cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler) (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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.impute._base.SimpleImputer (5)
Imputation transformer for completing missing values.
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sklearn.tree.tree.DecisionTreeClassifier (51)
A decision tree classifier.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)) (3)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler) (3)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.StandardScaler (31)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder) (3)
Automatically created scikit-learn flow.
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sklearn.preprocessing._encoders.OneHotEncoder (13)
Automatically created scikit-learn flow.
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sklearn.svm.classes.SVC (33)
Automatically created scikit-learn flow.
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__main__.MyLR (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(polynomialfeatures=sklearn.preprocessing.data.PolynomialFeatures,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.PolynomialFeatures (4)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier (1)
Automatically created scikit-learn flow.
6 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (25)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.DecisionTreeClassifier (41)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (17)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.DecisionTreeClassifier (16)
Automatically created scikit-learn flow.
31 runs0 likes0 downloads0 reach0 impact
sklearn.neighbors.classification.KNeighborsClassifier (18)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (11)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.imputation.Imputer (14)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.OneHotEncoder (15)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (30)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.ExtraTreeClassifier (9)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (1)
Flow generated by openml_run
18 runs0 likes2 downloads2 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (11)
Flow generated by openml_run
21 runs0 likes6 downloads6 reach17 impact