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study with illegal runs

study with illegal runs

Created 15-01-2024 by Continuous Integration Visibility: public
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TEST830fde6b02sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression) (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…
1 runs0 likes0 downloads0 reach0 impact
TEST13e8e7a5cdsklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier) (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…
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.preprocessing._data.StandardScaler,cat=sklearn.preprocessing._encoders.OneHotEncoder),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…
21 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(preprocess=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.preprocessing._encoders.OneHotEncoder,cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)),estimator=sklearn.tree._classes.DecisionTreeClassifier) (3)
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…
5 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(preprocess=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.preprocessing._encoders.OneHotEncoder,cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)),estimator=sklearn.tree._classes.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…
6 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,boosting=sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree._classes.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…
13 runs0 likes0 downloads0 reach0 impact