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sklearn.preprocessing.data.OneHotEncoder (26)
Automatically created scikit-learn flow.
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openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)) (1)
Automatically created scikit-learn flow.
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openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC) (3)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (10)
Automatically created scikit-learn flow.
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sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)) (2)
Automatically created scikit-learn flow.
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weka.classifiers.meta.multisearch.RandomSearch (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic)) (1)
Weka implementation.
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weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize) (1)
Weka implementation.
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weka.filters.unsupervised.attribute.ReplaceMissingValues (1)
Weka implementation.
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weka.filters.unsupervised.attribute.RemoveUseless (1)
Weka implementation.
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weka.filters.unsupervised.attribute.Normalize (1)
Weka implementation.
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weka.classifiers.functions.supportVector.RBFKernel (1)
Weka implementation.
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weka.classifiers.functions.Logistic (1)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)) (1)
Weka implementation.
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weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree) (1)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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weka.classifiers.trees.REPTree (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.Logistic) (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance))) (1)
Weka implementation.
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weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance)) (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance) (1)
Weka implementation.
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weka.core.EuclideanDistance (1)
Wikipedia. Euclidean distance. URL http://en.wikipedia.org/wiki/Euclidean_distance.
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weka.classifiers.bayes.NaiveBayes (1)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.trees.RandomForest) (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.trees.J48) (1)
Weka implementation.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (4)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (25)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (5)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (26)
Automatically created scikit-learn flow.
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sklearn.svm.classes.SVC (21)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (11)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,Categorial=sklearn.preprocessing.data.OneHotEncoder,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.weight_boosting.AdaBoostClassifier (8)
Automatically created scikit-learn flow.
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sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier) (6)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (27)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,Categorial=sklearn.preprocessing.data.OneHotEncoder,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (12)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,Categorial=sklearn.preprocessing.data.OneHotEncoder,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,scaler=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.linear_model.stochastic_gradient.SGDClassifier (7)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(normalizer=sklearn.preprocessing.data.Normalizer,featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.Normalizer (2)
Automatically created scikit-learn flow.
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sklearn.cluster.hierarchical.FeatureAgglomeration (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,normalizer=sklearn.preprocessing.data.Normalizer,functiontransformer=sklearn.preprocessing._function_transformer.FunctionTransformer,featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing._function_transformer.FunctionTransformer (3)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (13)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(1=sklearn.preprocessing.imputation.Imputer,2=sklearn.preprocessing.data.OneHotEncoder,3.0=sklearn.preprocessing._function_transformer.FunctionTransformer,5=sklearn.cluster.hierarchical.FeatureAgglomeration,6=sklearn.linear_model.stochastic_gradient.SGDClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,Categorial=sklearn.preprocessing.data.OneHotEncoder,estimator=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.ensemble.forest.RandomForestClassifier) (3)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.svm.classes.SVC) (3)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier) (7)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier) (2)
Automatically created scikit-learn flow.
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hyperimp.utils.preprocessing.ConditionalImputer (2)
Automatically created scikit-learn flow.
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sklearn.linear_model.logistic.LogisticRegression (15)
Automatically created scikit-learn flow.
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skopt.searchcv.BayesSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))) (1)
Automatically created scikit-learn flow.
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skopt.searchcv.BayesSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(steps__Imputer=sklearn.preprocessing.imputation.Imputer,steps__OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,steps__Classifier=sklearn.ensemble.forest.RandomForestClassifier) (2)
Automatically created sub-component.
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sklearn.preprocessing.imputation.Imputer (27)
Automatically created sub-component.
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sklearn.preprocessing.data.OneHotEncoder (27)
Automatically created sub-component.
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sklearn.ensemble.forest.RandomForestClassifier (42)
Automatically created sub-component.
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skopt.searchcv.BayesSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
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sklearn.linear_model.logistic.LogisticRegression (16)
Automatically created scikit-learn flow.
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mlr.classif.penalized.meanEncode.osw.scale (1)
Learner mlr.classif.penalized.meanEncode.osw.scale from package(s) !penalized.
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sklearn.ensemble.bagging.BaggingClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (28)
Automatically created scikit-learn flow.
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mlr.classif.ranger.meanEncode.osw.scale.collapse.fact.dropconst.dropnacols.inftona (1)
Learner mlr.classif.ranger.meanEncode.osw.scale.collapse.fact.dropconst.dropnacols.inftona from package(s) ranger.
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sklearn.tree.tree.ExtraTreeClassifier (19)
Automatically created scikit-learn flow.
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sklearn.preprocessing.imputation.Imputer (28)
Automatically created scikit-learn flow.
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sklearn.preprocessing._encoders.OneHotEncoder (2)
Automatically created scikit-learn flow.
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sklearn.tree.tree.ExtraTreeClassifier (20)
Automatically created scikit-learn flow.
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mlr.classif.randomForest.filtered (9)
Learner mlr.classif.randomForest.filtered from package(s) randomForest.
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mlr.classif.rpart.imputed.filtered (12)
Learner mlr.classif.rpart.imputed.filtered from package(s) rpart.
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sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler) (1)
Automatically created scikit-learn flow.
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sklearn.impute.MissingIndicator (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing.imputation.Imputer (29)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (14)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder) (1)
Automatically created scikit-learn flow.
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sklearn.impute.SimpleImputer (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing._encoders.OneHotEncoder (3)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (29)
Automatically created scikit-learn flow.
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sklearn.svm.classes.SVC (22)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),bernoullinb=sklearn.naive_bayes.BernoulliNB) (1)
Automatically created scikit-learn flow.
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sklearn.naive_bayes.BernoulliNB (5)
Automatically created scikit-learn flow.
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sklearn.neural_network.multilayer_perceptron.MLPClassifier (15)
Automatically created scikit-learn flow.
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sklearn.linear_model.stochastic_gradient.SGDClassifier (8)
Automatically created scikit-learn flow.
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sklearn.neighbors.classification.KNeighborsClassifier (30)
Automatically created scikit-learn flow.
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sklearn.ensemble.gradient_boosting.GradientBoostingClassifier (14)
Automatically created scikit-learn flow.
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sklearn.ensemble.forest.RandomForestClassifier (44)
Automatically created scikit-learn flow.
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sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier) (8)
Automatically created scikit-learn flow.
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sklearn.ensemble.forest.ExtraTreesClassifier (10)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (7)
Automatically created scikit-learn flow.
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sklearn.preprocessing.imputation.Imputer (30)
Automatically created scikit-learn flow.
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sklearn.tree.tree.DecisionTreeClassifier (30)
Automatically created scikit-learn flow.
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