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TESTde8c80bfa7sklearn.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
TESTdfe9cc4cdcsklearn.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
TEST488fde151csklearn.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
TESTa0a16eb00asklearn.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
TEST16bc15cf47sklearn.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
TEST9dea91da5bsklearn.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
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.naive_bayes.GaussianNB) (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…
1 runs0 likes0 downloads0 reach0 impact
TEST7de445048esklearn.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
TEST19dca0b4adsklearn.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
TEST1cd15f7fcfsklearn.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
TEST14609a458dsklearn.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
TESTa8d57c4462sklearn.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
TESTb0772af4besklearn.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
TEST584a61c714sklearn.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…
1 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.tree._classes.DecisionTreeClassifier)) (8)
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
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.naive_bayes.GaussianNB) (8)
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
TEST2c43c91a48sklearn.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
TEST3e56dfb0b1sklearn.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
TESTec64142224sklearn.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
TESTdd92911aacsklearn.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
TEST8cdb298ba4sklearn.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
TEST7058bf0679sklearn.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
TEST60310cb3ccsklearn.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…
1 runs0 likes0 downloads0 reach0 impact
TEST7295e8a9c4sklearn.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
TESTfb8f87f6aasklearn.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
TEST8de3d43c4csklearn.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
TESTd8ffa87180sklearn.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
TEST80d5dde16fsklearn.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
TESTc3b4c316f9sklearn.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
TEST8398d7fdd8sklearn.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
TESTe837c07a3fsklearn.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
TESTfbdf070a19sklearn.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
TEST9e13023e66sklearn.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
TEST6e94d85dd0sklearn.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
TEST9c8b0a80a5sklearn.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
TEST479e9c84b0sklearn.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
TEST80741a66f8sklearn.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
TESTb10b51f46asklearn.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
TESTf5a085d111sklearn.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
TESTc143be516esklearn.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
TESTef78935a7dsklearn.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
TESTc9e15df38asklearn.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
TEST4b3d45a920sklearn.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
TEST2ac3996730sklearn.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
TESTcfd20b5641sklearn.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…
1 runs0 likes0 downloads0 reach0 impact
TEST78e482b1a7sklearn.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…
1 runs0 likes0 downloads0 reach0 impact
TEST2902f4fea6sklearn.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
TEST080ac5a3d0sklearn.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
TEST88eea00fdbsklearn.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
TEST0b5970b6e7sklearn.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
TESTdfce362e54sklearn.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
TEST29327ea64esklearn.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
TEST04c22dfd2asklearn.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
TESTa63984184bsklearn.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
TEST1756f86982sklearn.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
TESTc2c892beecsklearn.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
TESTd87ad81ce3sklearn.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
TEST52f1e341b1sklearn.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
TESTTEST0b3ea1a1casklearn.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
TESTTEST3f300f1b50sklearn.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
TEST594eb26a4asklearn.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
TEST128ee2bfedsklearn.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
TESTd16e597141sklearn.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
TESTab4cb8ddfdsklearn.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…
1 runs0 likes0 downloads0 reach0 impact
TEST62f0469c02sklearn.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
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,boosting=sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree._classes.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…
1 runs0 likes0 downloads0 reach0 impact
TEST63ee7cb272sklearn.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
TEST862cc6d5b5sklearn.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
TEST8c577447d0sklearn.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
TEST1764d94b5asklearn.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
TEST304f7181e9sklearn.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
TEST6109a5331esklearn.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
TEST816018e188sklearn.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
TESTd53ac22126sklearn.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
TEST3d5ef1dd6dsklearn.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…
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TEST38df47a79bsklearn.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…
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TESTd383a595b5sklearn.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",…
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TEST3f9faa04f0sklearn.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",…
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TEST9726c377f0sklearn.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
TESTe8ee1ccdbdsklearn.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
TEST6907a44969sklearn.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…
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TEST4f7dc71d0esklearn.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.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.tree._classes.DecisionTreeClassifier)) (9)
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
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.tree._classes.DecisionTreeClassifier) (9)
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
TEST346b9df3fesklearn.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
TEST68219d3c4dsklearn.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
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.naive_bayes.GaussianNB) (9)
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
TEST48fa8e34besklearn.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",…
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TESTTESTd5477ebcc5sklearn.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…
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TESTTESTdc39c58acesklearn.tree._classes.DecisionTreeClassifier (1)
A decision tree classifier.
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TESTTEST466e44c066sklearn.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…
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sklearn.pipeline.Pipeline(enc=sklearn.preprocessing._encoders.OneHotEncoder,rs=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._forest.RandomForestClassifier)) (9)
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
TEST83dc153467sklearn.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
TEST2bb4e2754csklearn.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
TEST1f90c6ae14sklearn.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
TESTf85d0cdc96sklearn.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
TESTd36ebe6b22sklearn.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
TESTb70cd5c6ccsklearn.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
TESTc835e86bf1sklearn.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
TESTf67f8a5009sklearn.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