OpenML
Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.
1046 runs0 likes4 downloads4 reach621 impact
Webb, Geoffrey I., Boughton, Janice, Zheng, Fei, Ting, Kai Ming, Salem, Houssam (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive…
1039 runs0 likes2 downloads2 reach55 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
1014 runs0 likes3 downloads3 reach55 impact
Learner mlr.classif.glmnet from package(s) glmnet.
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Moa implementation of BlastWindowed
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Weka implementation of REPTree
932 runs0 likes11 downloads11 reach894 impact
Weka implementation of ZeroR
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Weka implementation of ZeroR
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le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
875 runs0 likes5 downloads5 reach875 impact
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
873 runs0 likes3 downloads3 reach276 impact
Weka implementation of SGD
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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,…
868 runs0 likes3 downloads3 reach831 impact
Weka implementation of SGD
856 runs0 likes2 downloads2 reach700 impact
Moa implementation of BlastWindowed
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Weka implementation of AttributeSelectedClassifier
839 runs0 likes2 downloads2 reach122 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
829 runs0 likes6 downloads6 reach56 impact
S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.
827 runs0 likes2 downloads2 reach6 impact
A Weka KnowledgeFlow using RandomForest.kf
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Learner mlr.classif.xgboost from package(s) xgboost.
819 runs0 likes0 downloads0 reach814 impact
A Weka KnowledgeFlow using AttributeSelection-BestFirst-CfsSubsetEval-KStar.kf
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A Weka KnowledgeFlow using Bagging-IBk5.kf
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A Weka KnowledgeFlow using AttributeSelection-Ranker-ReliefF-KStar.kf
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A Weka KnowledgeFlow using HoeffdingTree.kf
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A Weka KnowledgeFlow using JRip.kf
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A Weka KnowledgeFlow using AdaBoostM1-HoeffdingTree.kf
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A Weka KnowledgeFlow using AttributeSelection-BestFirst-CfsSubsetEval-Standardize-IBk5.kf
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A Weka KnowledgeFlow using AttributeSelection-Ranker-ReliefF-ReplaceMissingValues-NaiveBayes.kf
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A Weka KnowledgeFlow using ReplaceMissingValues-Standardize-NaiveBayes.kf
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A Weka KnowledgeFlow using Bagging-SMO.kf
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A Weka KnowledgeFlow using AdaBoostM1-IBk5.kf
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A Weka KnowledgeFlow using Bagging-NaiveBayes.kf
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Learner mlr.classif.xgboost from package(s) xgboost.
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A Weka KnowledgeFlow using AttributeSelection-Ranker-InfoGain-Standardize-IBk5.kf
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A Weka KnowledgeFlow using AttributeSelection-Ranker-ReliefF-Standardize-IBk5.kf
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A Weka KnowledgeFlow using ReplaceMissingValues-J48.kf
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A Weka KnowledgeFlow using AttributeSelection-Ranker-ReliefF-SMO.kf
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A Weka KnowledgeFlow using ZeroR.kf
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A Weka KnowledgeFlow using Bagging-HoeffdingTree.kf
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A Weka KnowledgeFlow using Bagging-JRip.kf
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A Weka KnowledgeFlow using AttributeSelection-Ranker-InfoGain-SMO.kf
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A Weka KnowledgeFlow using AdaBoostM1-SMO.kf
811 runs0 likes0 downloads0 reach0 impact
A Weka KnowledgeFlow using AttributeSelection-Ranker-InfoGain-ReplaceMissingValues-NaiveBayes.kf
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A Weka KnowledgeFlow using AdaBoostM1-J48.kf
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A Weka KnowledgeFlow using Bagging-J48.kf
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A Weka KnowledgeFlow using AttributeSelection-BestFirst-CfsSubsetEval-SMO.kf
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A Weka KnowledgeFlow using AttributeSelection-BestFirst-CfsSubsetEval-ReplaceMissingValues-NaiveBayes.kf
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A Weka KnowledgeFlow using ReplaceMissingValues-PKIDiscretize-NaiveBayes.kf
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A Weka KnowledgeFlow using RandomSubspace.kf
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A Weka KnowledgeFlow using Standardize-J48.kf
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A Weka KnowledgeFlow using AdaBoostM1-NaiveBayes.kf
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Webb, Geoffrey I., Boughton, Janice, Zheng, Fei, Ting, Kai Ming, Salem, Houssam (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive…
805 runs0 likes2 downloads2 reach49 impact
Learner mlr.classif.glmnet from package(s) glmnet.
796 runs0 likes0 downloads0 reach790 impact
Weka implementation of KernelLogisticRegression
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George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
786 runs0 likes16 downloads16 reach642 impact
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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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…
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Please use the mlr add-on code https://github.com/HeidiSeibold/sandbox/blob/95fb76a6c6c645dc5915754b739f2c00b12df542/rstuff/openml_ctree.R and devel partykit package revision 1034:…
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Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
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Weka implementation of FilteredClassifier
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R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
739 runs0 likes8 downloads8 reach648 impact
Flow generated by run_task
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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,…
698 runs0 likes3 downloads3 reach536 impact
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
694 runs0 likes3 downloads3 reach158 impact
Learner mlr.classif.ranger from package(s) ranger.
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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…
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D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
671 runs0 likes3 downloads3 reach515 impact
Moa implementation of AccuracyWeightedEnsemble
664 runs0 likes0 downloads0 reach0 impact
Pierre Geurts, Damien Ernst, Louis Wehenkel (2006). Extremely randomized trees. Machine Learning. 63(1):3-42.
636 runs0 likes2 downloads2 reach568 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
630 runs0 likes3 downloads3 reach598 impact
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
621 runs0 likes3 downloads3 reach502 impact
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
619 runs0 likes4 downloads4 reach55 impact
Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. In: Proceedings of the 5th International Conferenceon Discovery Science, 153-164, 2002.
616 runs0 likes2 downloads2 reach73 impact
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
615 runs0 likes4 downloads4 reach500 impact
Weka implementation of SGD
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Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and…
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Weka implementation of RandomCommittee
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Flow generated by run_task
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Learner mlr.classif.ranger.imputed.dummied.preproc from package(s) ranger.
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Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005. Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for…
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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…
557 runs0 likes0 downloads0 reach0 impact
A.K. Seewald, J. Fuernkranz: An Evaluation of Grading Classifiers. In: Advances in Intelligent Data Analysis: 4th International Conference, Berlin/Heidelberg/New York/Tokyo, 115-124, 2001.
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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…
547 runs0 likes3 downloads3 reach2 impact
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), 318-319, 2008.
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Weka implementation of IterativeClassifierOptimizer
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Ting, K. M., Witten, I. H.: Stacking Bagged and Dagged Models. In: Fourteenth international Conference on Machine Learning, San Francisco, CA, 367-375, 1997.
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Flow generated by run_task
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Weka implementation of AttributeSelectedClassifier
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Learner mlr.classif.svm from package(s) e1071.
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Weka implementation of MultiSearch
519 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003. P.…
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Weka implementation of FilteredClassifier
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Automatically created scikit-learn flow.
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Learner mlr.classif.kknn from package(s) !kknn.
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