Flow
ID's
Sort: most runs
18435 results
TEST7ffa519548sklearn.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
TESTe0aff75386sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST730dfaec5csklearn.linear_model._logistic.LogisticRegression (1)
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…
1 runs0 likes0 downloads0 reach0 impact
TESTd39b534a07sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "predict",…
1 runs0 likes0 downloads0 reach0 impact
TESTa91114934esklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST054e0d254csklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TEST3eb3b7288dsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TESTd507fa7e6csklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST08c33f8f11sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST56b12f4414sklearn.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,…
1 runs0 likes0 downloads0 reach0 impact
TESTf2081d62ecsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TESTc825719214sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST8db0b307casklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.tree._classes.DecisionTreeClassifier)) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTfa3b3b16c1sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST01af2977ddsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTfb2f30b34fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST3049498979sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST5af878149dsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTf8cd2f72f9sklearn.linear_model._logistic.LogisticRegression (1)
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…
1 runs0 likes0 downloads0 reach0 impact
TESTTESTf519cc47d3sklearn.naive_bayes.GaussianNB (1)
Gaussian Naive Bayes (GaussianNB) Can perform online updates to model parameters via :meth:`partial_fit`. For details on algorithm used to update feature means and variance online, see Stanford CS…
1 runs0 likes0 downloads0 reach0 impact
TESTfcf42b7ca0sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TESTTESTb040e5e56bsklearn.naive_bayes.GaussianNB (1)
Gaussian Naive Bayes (GaussianNB) Can perform online updates to model parameters via :meth:`partial_fit`. For details on algorithm used to update feature means and variance online, see Stanford CS…
1 runs0 likes0 downloads0 reach0 impact
TESTb28a0a4f2dsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST3d17d3b4a1sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TEST74ce60b4bcsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST94247229ebsklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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…
1 runs0 likes0 downloads0 reach0 impact
TEST05f1d61f89sklearn.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,…
1 runs0 likes0 downloads0 reach0 impact
TEST323fc77f43sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST62622f6052sklearn.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
TESTd74520d5a0sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST4a2c17ab94sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST2156ad4e47sklearn.linear_model._logistic.LogisticRegression (1)
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…
1 runs0 likes0 downloads0 reach0 impact
TESTc841b1808csklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "predict",…
1 runs0 likes0 downloads0 reach0 impact
TESTTEST3d309f93absklearn.tree._classes.DecisionTreeClassifier (1)
A decision tree classifier.
1 runs0 likes0 downloads0 reach0 impact
TEST9ebc645e18sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "predict",…
1 runs0 likes0 downloads0 reach0 impact
TESTbd87ed544esklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TESTd4fa7affa0sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTa29e15547asklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST8bb99ef68esklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTe9cf33ae11sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST6a226f47c8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TESTb0d13cb17dsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST854ad0d20esklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTe4ac5854b3sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTe8a5c8e63asklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST77772b8355sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST144dd1e8d2sklearn.linear_model._logistic.LogisticRegression (1)
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…
1 runs0 likes0 downloads0 reach0 impact
TESTTESTdc12553d89sklearn.naive_bayes.GaussianNB (1)
Gaussian Naive Bayes (GaussianNB) Can perform online updates to model parameters via :meth:`partial_fit`. For details on algorithm used to update feature means and variance online, see Stanford CS…
1 runs0 likes0 downloads0 reach0 impact
TEST8b0a984f70sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TESTTESTa464227619sklearn.tree._classes.DecisionTreeClassifier (1)
A decision tree classifier.
1 runs0 likes0 downloads0 reach0 impact
TESTcdac7b8cb5sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST336e1a0196sklearn.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,…
1 runs0 likes0 downloads0 reach0 impact
TESTTEST133eea06c7sklearn.naive_bayes.GaussianNB (1)
Gaussian Naive Bayes (GaussianNB) Can perform online updates to model parameters via :meth:`partial_fit`. For details on algorithm used to update feature means and variance online, see Stanford CS…
1 runs0 likes0 downloads0 reach0 impact
TESTe904e7772csklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.tree._classes.DecisionTreeClassifier) (11)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.naive_bayes.GaussianNB) (11)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTa555deac09sklearn.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
TESTc833f9182bsklearn.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
TEST662bc07965sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTea4bd2689fsklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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…
1 runs0 likes0 downloads0 reach0 impact
TEST872fcec363sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTd74f13a5a2sklearn.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
TESTf28de4c26asklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TEST94a63fbd42sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTa47ac196cesklearn.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
TESTe4b54ddf44sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST79774c834csklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TEST1a0dbd54cesklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.tree._classes.DecisionTreeClassifier)) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTb927f0543asklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST72b54ac9edsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTc608172fecsklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=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…
1 runs0 likes0 downloads0 reach0 impact
TEST310353c51bsklearn.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
TEST5b8cfe81ddsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST71baa0da1asklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST83ad5c664fsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST31ebc2aee9sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTbbfc7672b5sklearn.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
TEST8d5c099aabsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTdb2de31822sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,regressor=sklearn.linear_model._base.LinearRegression) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTfa6990498csklearn.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
TEST3f22b06868sklearn.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,…
1 runs0 likes0 downloads0 reach0 impact
TESTb80bef78d5sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TESTf08bf5ad0bsklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=sklearn.dummy.DummyClassifier) (1)
A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with…
1 runs0 likes0 downloads0 reach0 impact
TEST6d2b791c70sklearn.linear_model._logistic.LogisticRegression (1)
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…
1 runs0 likes0 downloads0 reach0 impact
TESTdcf31584b7sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST0e4f777990sklearn.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,…
1 runs0 likes0 downloads0 reach0 impact
TEST7ca5b4682fsklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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…
1 runs0 likes0 downloads0 reach0 impact
TEST498a87d300sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TEST498ca8377bsklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST4d2289e823sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
1 runs0 likes0 downloads0 reach0 impact
TESTc1f62ca558sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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…
1 runs0 likes0 downloads0 reach0 impact
TEST2b34ba3ecbsklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST1dac27fb53sklearn.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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST51a11fe38esklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TESTa9960b4372sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,dummy=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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST0dd5e94e1dsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TEST44a60b17ffsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
1 runs0 likes0 downloads0 reach0 impact
TESTeb54580f3dsklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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 fit…
1 runs0 likes0 downloads0 reach0 impact
TEST43c5b92233sklearn.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
TEST46672aa265sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(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…
1 runs0 likes0 downloads0 reach0 impact