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weka.MultiBoostAB_JRip (3)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
42 runs0 likes0 downloads0 reach0 impact
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)),kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
42 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(anothersimpleimputer=__main__.AnotherSimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
42 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=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…
42 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC) (3)
Automatically created scikit-learn flow.
42 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dimension_reduction=sklearn.decomposition.pca.PCA,scaler=sklearn.preprocessing.data.MinMaxScaler,forest=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
42 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (66)
A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive…
42 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_ZeroR (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_OneR (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_SMO_RBFKernel (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_LMT (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_Bagging_LWL_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_LWL_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_CVParameterSelection_ZeroR (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.MultiBoostAB_OneR (3)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_REPTree (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
41 runs0 likes0 downloads0 reach1 impact
weka.BFTree (2)
Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ. Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of…
41 runs0 likes2 downloads2 reach40 impact
weka.LMT (2)
Niels Landwehr, Mark Hall, Eibe Frank (2005). Logistic Model Trees. Machine Learning. 95(1-2):161-205. Marc Sumner, Eibe Frank, Mark Hall: Speeding up Logistic Model Tree Induction. In: 9th European…
41 runs0 likes2 downloads2 reach36 impact
weka.LWL_J48 (2)
Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes. In: 19th Conference in Uncertainty in Artificial Intelligence, 249-256, 2003. C. Atkeson, A. Moore, S. Schaal (1996). Locally…
41 runs0 likes2 downloads2 reach39 impact
weka.MultiBoostAB_IBk (2)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
41 runs0 likes2 downloads2 reach4 impact
weka.MultiBoostAB_JRip (2)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
41 runs0 likes2 downloads2 reach35 impact
weka.MultiBoostAB_RandomForest (2)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
41 runs0 likes2 downloads2 reach35 impact
classif.IBk (1)
Learner classif.IBk from package(s) RWeka.
41 runs0 likes1 downloads1 reach0 impact
weka.DecisionTable_BestFirst (6)
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
41 runs0 likes4 downloads4 reach30 impact
sklearn.tree._classes.DecisionTreeClassifier (2)
A decision tree classifier.
41 runs0 likes0 downloads0 reach35 impact
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.multi_column_label_encoder.MultiColumnLabelEncoderComponent,step_1=sklearn.ensemble._forest.RandomForestClassifier) (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…
41 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (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…
41 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_Bagging_LMT (1)
Weka implementation of FilteredClassifier
41 runs0 likes0 downloads0 reach39 impact
weka.AttributeSelectedClassifier_JRip (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_REPTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_BayesNet (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_A1DE (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_IBk (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_J48 (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_NaiveBayes (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_AdaBoostM1_OneR (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_REPTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_IBk (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_Bagging_J48 (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_JRip (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_NaiveBayes (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_OneR (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_NaiveBayesUpdateable (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_KStar (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_LWL_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_ClassificationViaRegression_M5P (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Dagging_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.Dagging_DecisionStump (4)
Ting, K. M., Witten, I. H.: Stacking Bagged and Dagged Models. In: Fourteenth international Conference on Machine Learning, San Francisco, CA, 367-375, 1997.
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_END_ND_J48 (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_IterativeClassifierOptimizer_LogitBoost_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_RacedIncrementalLogitBoost_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_RandomCommittee_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_RandomSubSpace_REPTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_LogitBoost_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_NaiveBayes (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_JRip (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_OneR (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_J48 (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.MultiBoostAB_J48 (3)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_MultiBoostAB_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.MultiBoostAB_RandomTree (3)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_DTNB (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_PART (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_LADTree (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_LMT (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_NBTree (1)
Weka implementation of AttributeSelectedClassifier
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weka.AttributeSelectedClassifier_RandomTree (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_SimpleLogistic (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
40 runs0 likes0 downloads0 reach0 impact
weka.MultiBoostAB_BFTree (2)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
40 runs0 likes2 downloads2 reach35 impact
weka.Bagging (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
40 runs0 likes1 downloads1 reach0 impact
moa.WeightedEnsemble (1)
Moa implementation of WeightedEnsemble
40 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(step_0=sklearn.linear_model._stochastic_gradient.SGDClassifier) (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…
40 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_AttributeSelectedClassifier_RandomCommittee_RandomTree (1)
Weka implementation of FilteredClassifier
40 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier) (3)
Automatically created scikit-learn flow.
40 runs0 likes1 downloads1 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Flatten,Dense,Dropout,Dense,Dropout,Dense) (1)
Automatically created scikit-learn flow.
40 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.StandardScaler,step_1=sklearn.ensemble._forest.RandomForestClassifier) (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…
40 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._factor_analysis.FactorAnalysis,step_1=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (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…
40 runs0 likes0 downloads0 reach0 impact
mlr.classif.rpart (11)
Learner mlr.classif.rpart from package(s) rpart.
39 runs0 likes0 downloads0 reach38 impact
weka.FilteredClassifier_ReplaceMissingValues_HNB (1)
Weka implementation of FilteredClassifier
39 runs0 likes2 downloads2 reach1 impact
weka.BayesNet_K2 (19)
Weka implementation of BayesNet
39 runs0 likes1 downloads1 reach0 impact
classif.neuralnet (4)
Learner classif.neuralnet from package(s) neuralnet.
39 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.svm._classes.SVC) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
39 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_RandomCommittee_RandomTree (1)
Weka implementation of FilteredClassifier
39 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_AttributeSelectedClassifier_RandomSubSpace_REPTree (1)
Weka implementation of FilteredClassifier
39 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (10)
Automatically created scikit-learn flow.
39 runs0 likes1 downloads1 reach38 impact
weka.NaiveBayes (18)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
39 runs0 likes0 downloads0 reach38 impact
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense) (1)
Automatically created scikit-learn flow.
39 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,step_1=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…
39 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(step_0=automl.util.sklearn.StackingEstimator(estimator=sklearn.ensemble._forest.RandomForestClassifier),step_1=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…
39 runs0 likes0 downloads0 reach0 impact
sklearn.svm.classes.SVC (45)
C-Support Vector Classification. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to dataset with more than…
39 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.DecisionTreeClassifier (65)
A decision tree classifier.
39 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_Bagging_J48 (2)
Weka implementation of FilteredClassifier
38 runs0 likes0 downloads0 reach37 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.tree.tree.DecisionTreeClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
38 runs0 likes0 downloads0 reach0 impact