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sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier) (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…
296 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (16)
Automatically created sub-component.
295 runs0 likes2 downloads2 reach292 impact
classif.ksvm (4)
Learner classif.ksvm from package(s) kernlab.
295 runs0 likes1 downloads1 reach0 impact
classif.naiveBayes (5)
Learner classif.naiveBayes from package(s) e1071.
295 runs0 likes1 downloads1 reach0 impact
classif.nnet (3)
Learner classif.nnet from package(s) nnet.
295 runs0 likes1 downloads1 reach0 impact
classif.OneR (4)
Learner classif.OneR from package(s) RWeka.
293 runs0 likes1 downloads1 reach0 impact
classif.boosting (4)
Learner classif.boosting from package(s) adabag, rpart.
293 runs0 likes1 downloads1 reach0 impact
classif.multinom (5)
Learner classif.multinom from package(s) nnet.
293 runs0 likes1 downloads1 reach0 impact
classif.rpart (38)
Learner classif.rpart from package(s) rpart.
293 runs0 likes2 downloads2 reach1 impact
classif.glmnet (1)
Learner classif.glmnet from package(s) !glmnet.
292 runs0 likes1 downloads1 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
292 runs0 likes0 downloads0 reach0 impact
weka.MultilayerPerceptron (8)
Weka implementation of MultilayerPerceptron
291 runs0 likes0 downloads0 reach287 impact
classif.PART (4)
Learner classif.PART from package(s) RWeka.
291 runs0 likes1 downloads1 reach0 impact
classif.randomForest (42)
Learner classif.randomForest from package(s) randomForest.
291 runs0 likes1 downloads1 reach0 impact
moa.NaiveBayes (1)
Moa implementation of NaiveBayes
291 runs0 likes14 downloads14 reach78 impact
weka.BayesNet (1)
Weka implementation of BayesNet
290 runs0 likes0 downloads0 reach2 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)) (1)
Automatically created scikit-learn flow.
288 runs0 likes0 downloads0 reach0 impact
classif.randomForestSRC (5)
Learner classif.randomForestSRC from package(s) randomForestSRC.
286 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier) (24)
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…
286 runs0 likes0 downloads0 reach16 impact
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neural_network._multilayer_perceptron.MLPClassifier) (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…
286 runs0 likes0 downloads0 reach0 impact
classif.ranger (3)
Learner classif.ranger from package(s) ranger.
285 runs0 likes1 downloads1 reach0 impact
weka.LMT (1)
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…
284 runs0 likes2 downloads2 reach0 impact
classif.cforest (4)
Learner classif.cforest from package(s) party.
284 runs0 likes1 downloads1 reach0 impact
classif.xgboost (4)
Learner classif.xgboost from package(s) xgboost.
283 runs0 likes1 downloads1 reach0 impact
classif.rda (4)
Learner classif.rda from package(s) klaR.
280 runs0 likes1 downloads1 reach0 impact
moa.LeveragingBag_kNN (1)
Moa implementation of LeveragingBag
280 runs0 likes2 downloads2 reach41 impact
weka.MultiSearch_SMO_RBFKernel (1)
Weka implementation of MultiSearch
279 runs0 likes1 downloads1 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) (2)
Automatically created scikit-learn flow.
279 runs0 likes1 downloads1 reach0 impact
weka.FilteredClassifier_SMO_PolyKernel (1)
Weka implementation of FilteredClassifier
277 runs0 likes0 downloads0 reach267 impact
weka.BayesianLogisticRegression (2)
Alexander Genkin, David D. Lewis, David Madigan (2004). Large-scale bayesian logistic regression for text categorization. URL http://www.stat.rutgers.edu/~madigan/PAPERS/shortFat-v3a.pdf.
277 runs0 likes1 downloads1 reach0 impact
moa.LeveragingBag_HoeffdingTree (2)
Moa implementation of LeveragingBag
277 runs0 likes2 downloads2 reach70 impact
classif.lda (9)
Learner classif.lda from package(s) MASS.
276 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.tree.tree.DecisionTreeClassifier) (4)
Automatically created scikit-learn flow.
273 runs0 likes0 downloads0 reach0 impact
weka.A1DE (2)
G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24.
272 runs0 likes2 downloads2 reach33 impact
weka.OLM (4)
Arie Ben-David (1992). Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications. Decision Sciences. 23:1357-1372.
272 runs0 likes3 downloads3 reach3 impact
weka.HyperPipes (2)
Weka implementation of HyperPipes
270 runs0 likes2 downloads2 reach36 impact
weka.FURIA (2)
Jens Christian Huehn, Eyke Huellermeier (2009). FURIA: An Algorithm for Unordered Fuzzy Rule Induction. Data Mining and Knowledge Discovery..
270 runs0 likes2 downloads2 reach35 impact
moa.HoeffdingTree (1)
A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not…
270 runs0 likes8 downloads8 reach53 impact
weka.AttributeSelectedClassifier (2)
Weka implementation of AttributeSelectedClassifier
270 runs0 likes0 downloads0 reach270 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier) (25)
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…
270 runs0 likes0 downloads0 reach3 impact
weka.ConjunctiveRule (4)
Weka implementation of ConjunctiveRule
269 runs0 likes2 downloads2 reach27 impact
weka.Bagging_J48 (5)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
268 runs0 likes2 downloads2 reach55 impact
weka.AttributeSelectedClassifier_SMO_PolyKernel (2)
Weka implementation of AttributeSelectedClassifier
266 runs0 likes0 downloads0 reach264 impact
weka.Bagging_JRip (3)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
266 runs0 likes2 downloads2 reach266 impact
weka.AdaBoostM1_NaiveBayes (3)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
265 runs0 likes0 downloads0 reach7 impact
moa.HoeffdingAdaptiveTree (1)
Moa implementation of HoeffdingAdaptiveTree
262 runs0 likes8 downloads8 reach48 impact
moa.LeveragingBag_HoeffdingTree (1)
Moa implementation of LeveragingBag
260 runs0 likes2 downloads2 reach40 impact
weka.Ridor (4)
Weka implementation of Ridor
258 runs0 likes2 downloads2 reach37 impact
moa.kNN (1)
Moa implementation of kNN
258 runs0 likes3 downloads3 reach41 impact
weka.SimpleCart (4)
Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone (1984). Classification and Regression Trees. Wadsworth International Group, Belmont, California.
257 runs0 likes2 downloads2 reach14 impact
moa.OzaBag_HoeffdingTree (1)
Moa implementation of OzaBag
257 runs0 likes4 downloads4 reach54 impact
weka.FilteredClassifier_AttributeSelectedClassifier_IBk (1)
Weka implementation of FilteredClassifier
256 runs0 likes0 downloads0 reach256 impact
weka.KStar (4)
John G. Cleary, Leonard E. Trigg: K*: An Instance-based Learner Using an Entropic Distance Measure. In: 12th International Conference on Machine Learning, 108-114, 1995.
256 runs0 likes1 downloads1 reach249 impact
weka.FilteredClassifier_IBk (1)
Weka implementation of FilteredClassifier
253 runs0 likes0 downloads0 reach252 impact
moa.LeveragingBag_HoeffdingTree (4)
Moa implementation of LeveragingBag
252 runs0 likes0 downloads0 reach2 impact
weka.BayesNet_K2 (1)
Weka implementation of BayesNet
252 runs0 likes7 downloads7 reach222 impact
moa.OzaBoost_HoeffdingTree (1)
Moa implementation of OzaBoost
252 runs0 likes4 downloads4 reach46 impact
moa.OzaBag_HoeffdingTree (6)
Moa implementation of OzaBag
248 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_IBk (2)
Weka implementation of AttributeSelectedClassifier
246 runs0 likes0 downloads0 reach246 impact
moa.ASHoeffdingTree (1)
Moa implementation of ASHoeffdingTree
246 runs0 likes2 downloads2 reach45 impact
moa.MajorityClass (1)
Moa implementation of MajorityClass
246 runs0 likes2 downloads2 reach48 impact
weka.NBTree (6)
Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.
245 runs0 likes2 downloads2 reach25 impact
moa.RandomHoeffdingTree (1)
Moa implementation of RandomHoeffdingTree
245 runs0 likes4 downloads4 reach39 impact
moa.NoChange (1)
Moa implementation of NoChange
245 runs0 likes2 downloads2 reach44 impact
moa.SPegasos (1)
Moa implementation of SPegasos
245 runs0 likes2 downloads2 reach36 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created scikit-learn flow.
242 runs0 likes0 downloads0 reach0 impact
moa.LeveragingBag_HoeffdingOptionTree (1)
Moa implementation of LeveragingBag
241 runs0 likes0 downloads0 reach237 impact
moa.OzaBag_HoeffdingTree (4)
Moa implementation of OzaBag
240 runs0 likes1 downloads1 reach0 impact
weka.RBFNetwork (9)
Weka implementation of RBFNetwork
240 runs0 likes2 downloads2 reach37 impact
sklearn.ensemble.forest.RandomForestClassifier (32)
Automatically created scikit-learn flow.
239 runs0 likes1 downloads1 reach241 impact
classif.mda (1)
Learner classif.mda from package(s) !mda.
237 runs0 likes1 downloads1 reach0 impact
moa.OzaBag_HoeffdingOptionTree (1)
Moa implementation of OzaBag
236 runs0 likes0 downloads0 reach232 impact
weka.BFTree (4)
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…
236 runs0 likes2 downloads2 reach13 impact
weka.A1DE (28)
G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24.
233 runs0 likes2 downloads2 reach1 impact
classif.ada (5)
Learner classif.ada from package(s) ada.
233 runs0 likes1 downloads1 reach0 impact
weka.ZeroR (1)
Weka implementation of ZeroR
232 runs0 likes4 downloads4 reach200 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
231 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.neural_network.multilayer_perceptron.MLPClassifier)) (1)
Automatically created scikit-learn flow.
231 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_JRip (3)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
230 runs0 likes1 downloads1 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) (4)
Automatically created scikit-learn flow.
230 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (15)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
229 runs0 likes0 downloads0 reach192 impact
weka.FilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel (1)
Weka implementation of FilteredClassifier
228 runs0 likes0 downloads0 reach228 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC) (4)
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…
228 runs0 likes0 downloads0 reach0 impact
weka.MultilayerPerceptronCS (1)
Weka implementation of MultilayerPerceptronCS
227 runs0 likes2 downloads2 reach183 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
223 runs0 likes0 downloads0 reach0 impact
weka.IBk (14)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
221 runs0 likes0 downloads0 reach214 impact
classif.binomial (5)
Learner classif.binomial from package(s) stats.
220 runs0 likes1 downloads1 reach0 impact
weka.Bagging_IBk (2)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
219 runs0 likes2 downloads2 reach48 impact
sklearn.svm.classes.SVC (35)
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…
219 runs0 likes0 downloads0 reach0 impact
openmlpimp.sklearn.beam_search.BeamSearchCV(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.
218 runs0 likes0 downloads0 reach0 impact
classif.probit (3)
Learner classif.probit from package(s) stats.
215 runs0 likes1 downloads1 reach0 impact
classif.plr (4)
Learner classif.plr from package(s) stepPlr.
214 runs0 likes1 downloads1 reach0 impact
classif.blackboost (2)
Learner classif.blackboost from package(s) mboost, party.
213 runs0 likes1 downloads1 reach0 impact
classif.randomForest (43)
Learner classif.randomForest from package(s) randomForest.
213 runs0 likes12 downloads12 reach204 impact
weka.BayesNet_K2 (2)
Weka implementation of BayesNet
210 runs0 likes4 downloads4 reach22 impact
weka.SPegasos (6)
S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.
210 runs0 likes2 downloads2 reach58 impact
classif.logreg (7)
Learner classif.logreg from package(s) stats.
210 runs0 likes1 downloads1 reach0 impact
classif.glmboost (2)
Learner classif.glmboost from package(s) mboost.
209 runs0 likes1 downloads1 reach0 impact
weka.AttributeSelectedClassifier_MultilayerPerceptron (1)
Weka implementation of AttributeSelectedClassifier
208 runs0 likes1 downloads1 reach0 impact
weka.IB1 (2)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
206 runs0 likes2 downloads2 reach39 impact