OpenML
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21333 results
classif.sda (7)
Learner classif.sda from package(s) sda.
96 runs0 likes1 downloads1 reach0 impact
classif.saeDNN (5)
Learner classif.saeDNN from package(s) deepnet.
97 runs0 likes1 downloads1 reach0 impact
classif.sparseLDA (3)
Learner classif.sparseLDA from package(s) !sparseLDA, MASS, !elasticnet.
88 runs0 likes1 downloads1 reach0 impact
classif.xyf (4)
Learner classif.xyf from package(s) kohonen.
100 runs0 likes1 downloads1 reach0 impact
matrixnet_on_MagicTelescope_implementation (1)
implementation for uploading results of instrument *matrixnet* on dataset *MagicTelescope*
12 runs0 likes1 downloads1 reach0 impact
weka.ZeroR (11)
Weka implementation of ZeroR
2 runs0 likes1 downloads1 reach0 impact
classif.randomForest (46)
Learner classif.randomForest from package(s) randomForest.
5 runs0 likes1 downloads1 reach0 impact
moa.NaiveBayes (3)
Moa implementation of NaiveBayes
3 runs0 likes1 downloads1 reach0 impact
classif.rpart (42)
Learner classif.rpart from package(s) rpart.
1 runs0 likes1 downloads1 reach0 impact
classif.randomForest (47)
Learner classif.randomForest from package(s) randomForest.
2 runs0 likes1 downloads1 reach0 impact
classif.randomForest (48)
Learner classif.randomForest from package(s) randomForest.
1 runs0 likes1 downloads1 reach0 impact
moa.NaiveBayesMultinomial (2)
Moa implementation of NaiveBayesMultinomial
1 runs0 likes1 downloads1 reach0 impact
weka.Stacking_J48 (2)
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
132 runs0 likes1 downloads1 reach131 impact
classif.rpart (43)
Learner classif.rpart from package(s) rpart.
1 runs0 likes1 downloads1 reach0 impact
classif.PART.bagged (1)
Learner classif.PART.bagged from package(s) RWeka.
1 runs0 likes1 downloads1 reach0 impact
classif.naiveBayes.bagged (1)
Learner classif.naiveBayes.bagged from package(s) e1071.
2 runs0 likes1 downloads1 reach0 impact
classif.J48.bagged (1)
Learner classif.J48.bagged from package(s) RWeka.
1 runs0 likes1 downloads1 reach0 impact
classif.naiveBayes.bagged (2)
Learner classif.naiveBayes.bagged from package(s) e1071.
1 runs0 likes1 downloads1 reach0 impact
moa.StackingAttemptV2_Perceptron (2)
Moa implementation of StackingAttemptV2
1 runs0 likes1 downloads1 reach0 impact
moa.StackingAttemptV2_SPegasos (2)
Moa implementation of StackingAttemptV2
1 runs0 likes1 downloads1 reach0 impact
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_NaiveBayes (4)
Weka implementation of AttributeSelectedClassifier
1 runs0 likes1 downloads1 reach0 impact
classif.knn (1)
Learner classif.knn from package(s) class.
17 runs0 likes1 downloads1 reach0 impact
moa.BlastDecayed (5)
Moa implementation of BlastDecayed
1 runs0 likes1 downloads1 reach0 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
openml.evaluation.EuclideanDistance (1)
An implementation of the evaluation measure "EuclideanDistance"
0 runs0 likes1 downloads1 reach0 impact
openml.evaluation.PolynomialKernel (1)
An implementation of the evaluation measure "PolynomialKernel"
0 runs0 likes1 downloads1 reach0 impact
openml.evaluation.area_under_roc_curve (1)
An implementation of the evaluation measure "area_under_roc_curve"
1 runs0 likes1 downloads1 reach1 impact
moa.AMRules (1)
Moa implementation of AMRules
13 runs0 likes1 downloads1 reach0 impact
moa.RandomRules_AMRules (1)
Moa implementation of RandomRules
16 runs0 likes1 downloads1 reach0 impact
automlbenchmark_autoweka (1)
Auto-WEKA 2.6 as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
17 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(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…
92 runs0 likes1 downloads1 reach0 impact
sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier) (3)
Randomized search on hyper parameters. The search strategy starts evaluating all the candidates with a small amount of resources and iteratively selects the best candidates, using more and more…
369 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (6)
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…
45 runs0 likes1 downloads1 reach44 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC) (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 fit…
1 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(Shapley-Blackbox=Framework.custom_sklearn_pipeline.CustomPipelineModel) (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…
3 runs0 likes1 downloads1 reach0 impact
Framework.building_blocks.EnsembleBlock (1)
Ensemble Model
0 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (2)
Automatically created scikit-learn flow.
2 runs0 likes1 downloads1 reach0 impact
GA.mlr.classif.J48.imputed.preproc.tuned (1)
Learner mlr.classif.J48 from package RWeka optimized by a Genetic Algorithm technique from package GA.
0 runs0 likes1 downloads1 reach0 impact
J48Bagging (1)
Just a 48Bagging workflow done with the KF.
23 runs0 likes1 downloads1 reach0 impact
decisionStump (1)
A flow using decisionStump for the POC.
17 runs0 likes1 downloads1 reach0 impact
j48 (1)
A flow using j48 for the POC.
16 runs0 likes1 downloads1 reach0 impact
smo (1)
A flow using smo for the POC.
29 runs0 likes1 downloads1 reach0 impact
mlr.classif.xgboost (8)
Learner mlr.classif.xgboost from package(s) xgboost.
1 runs0 likes1 downloads1 reach0 impact
mlr.classif.svm (11)
Learner mlr.classif.svm from package(s) e1071.
1 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
15 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
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
rm.process.polynomial_by_binomial_classification_support_vector_machine (4)
A RapidMiner Workflow.
6 runs1 likes1 downloads2 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (10)
Automatically created scikit-learn flow.
2 runs0 likes1 downloads1 reach2 impact
mlr.classif.h2o.randomForest (1)
Learner mlr.classif.h2o.randomForest from package(s) h2o.
1 runs0 likes1 downloads1 reach0 impact
mlr.classif.ranger (16)
Learner mlr.classif.ranger from package(s) ranger.
64882 runs0 likes1 downloads1 reach64862 impact
openmlstudy14.preprocessing.ConditionalImputer (6)
Automatically created scikit-learn flow.
0 runs0 likes1 downloads1 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (32)
Automatically created scikit-learn flow.
239 runs0 likes1 downloads1 reach241 impact
sklearn.linear_model.logistic.LogisticRegression (10)
Automatically created scikit-learn flow.
39 runs0 likes1 downloads1 reach38 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.tree.tree.DecisionTreeClassifier)) (1)
Automatically created scikit-learn flow.
595 runs0 likes1 downloads1 reach0 impact
weka.kf.ReplaceMissingValues-PKIDiscretize-NaiveBayes (1)
A Weka KnowledgeFlow using ReplaceMissingValues-PKIDiscretize-NaiveBayes.kf
815 runs0 likes1 downloads1 reach7 impact
weka.kf.Bagging-IBk5 (1)
A Weka KnowledgeFlow using Bagging-IBk5.kf
818 runs0 likes1 downloads1 reach7 impact
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) (1)
Automatically created scikit-learn flow.
73428 runs0 likes1 downloads1 reach28 impact
mlr.regr.rpart.dummied (1)
Learner mlr.regr.rpart.dummied from package(s) rpart.
79 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
63950 runs0 likes1 downloads1 reach0 impact
weka.Vote (1)
Ludmila I. Kuncheva (2004). Combining Pattern Classifiers: Methods and Algorithms. John Wiley and Sons, Inc.. J. Kittler, M. Hatef, Robert P.W. Duin, J. Matas (1998). On combining classifiers. IEEE…
121 runs0 likes1 downloads1 reach121 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (2)
Automatically created scikit-learn flow.
84614 runs0 likes1 downloads1 reach0 impact
sklearn.neighbors._classification.KNeighborsClassifier (6)
Classifier implementing the k-nearest neighbors vote.
1 runs0 likes1 downloads1 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(minmaxscaler=sklearn.preprocessing._data.MinMaxScaler,powertransformer=sklearn.preprocessing._data.PowerTransformer,robustscaler=sklearn.preprocessing._data.RobustScaler,standardscaler=sklearn.preprocessing._data.StandardScaler,randomforestclassifier=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 likes1 downloads1 reach0 impact
mlr.classif.randomForest (51)
Learner mlr.classif.randomForest from package(s) randomForest.
0 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier) (13)
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…
23 runs0 likes1 downloads1 reach18 impact
sklearn.pipeline.Pipeline(pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (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…
33 runs0 likes1 downloads1 reach0 impact
sklearn.pipeline.Pipeline(StandardScaler=sklearn.preprocessing._data.StandardScaler,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…
4 runs0 likes1 downloads1 reach0 impact
classif.randomForest (52)
Learner classif.randomForest from package(s) randomForest.
0 runs0 likes0 downloads0 reach0 impact
classif.randomForest (53)
Learner classif.randomForest from package(s) randomForest.
0 runs0 likes0 downloads0 reach0 impact
classif.rpart (46)
Learner classif.rpart from package(s) rpart.
0 runs0 likes0 downloads0 reach0 impact
weka.Bagging_REPTree (21)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.SMO_PolyKernel (13)
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
0 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_DecisionStump (15)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.Bagging_RandomForest (10)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.Bagging_IBk (3)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
175 runs0 likes0 downloads0 reach175 impact
weka.MathParameter (1)
Weka implementation of MathParameter
0 runs0 likes0 downloads0 reach0 impact
weka.J48 (35)
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
0 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1 (2)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.SMO (1)
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
0 runs0 likes0 downloads0 reach0 impact
moa.HoeffdingTree (6)
Moa implementation of HoeffdingTree
0 runs0 likes0 downloads0 reach0 impact
weka.SMO_RBFKernel (5)
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
0 runs0 likes0 downloads0 reach0 impact
mlr.classif.rpart (1)
Learner mlr.classif.rpart from package(s) rpart.
0 runs0 likes0 downloads0 reach0 impact
mlr.classif.randomForest.filtered.oversampled (2)
Learner mlr.classif.randomForest.filtered.oversampled from package(s) mlr, randomForestSRC, randomForest.
0 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_SMO_PolyKernel (1)
Weka implementation of AttributeSelectedClassifier
136 runs0 likes0 downloads0 reach0 impact
weka.SMO_PolyKernel (14)
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
0 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_J48 (1)
Weka implementation of AttributeSelectedClassifier
140 runs0 likes0 downloads0 reach3 impact
mlr.classif.randomForest.filtered (4)
Learner mlr.classif.randomForest.filtered from package(s) randomForestSRC, randomForest.
0 runs0 likes0 downloads0 reach0 impact
mlr.classif.rpart (3)
Learner mlr.classif.rpart from package(s) rpart.
0 runs0 likes0 downloads0 reach0 impact
mlr.classif.rpart.preproc (2)
Learner mlr.classif.rpart.preproc from package(s) rpart.
0 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_JRip (1)
Weka implementation of AttributeSelectedClassifier
40 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999openml.sklearn.model_selection.KFold (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.pipeline.Pipeline(sklearn.preprocessing.data.OneHotEncoder__sklearn.preprocessing.data.StandardScaler__sklearn.pipeline.FeatureUnion(sklearn.preprocessing.data.PolynomialFeatures__sklearn.decomposition.pca.PCA)__sklearn.ensemble.weight_boosting.AdaBoostClassifier(sklearn.tree.tree.DecisionTreeClassifier)) (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.preprocessing.data.OneHotEncoder (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.preprocessing.data.StandardScaler (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.pipeline.FeatureUnion(sklearn.preprocessing.data.PolynomialFeatures__sklearn.decomposition.pca.PCA) (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.preprocessing.data.PolynomialFeatures (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.decomposition.pca.PCA (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.ensemble.weight_boosting.AdaBoostClassifier(sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
325b3936TESTSENTINEL999sklearn.tree.tree.DecisionTreeClassifier (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact