Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
138 runs0 likes0 downloads0 reach0 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.
137 runs0 likes0 downloads0 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
137 runs0 likes0 downloads0 reach0 impact
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,…
137 runs0 likes2 downloads2 reach118 impact
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
137 runs0 likes0 downloads0 reach117 impact
Weka implementation of AttributeSelectedClassifier
136 runs0 likes0 downloads0 reach0 impact
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…
136 runs0 likes0 downloads0 reach0 impact
R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
136 runs0 likes0 downloads0 reach136 impact
Learner classif.randomForestSRC from package(s) randomForestSRC.
136 runs0 likes1 downloads1 reach0 impact
E. Frank, Y. Wang, S. Inglis, G. Holmes, I.H. Witten (1998). Using model trees for classification. Machine Learning. 32(1):63-76.
135 runs0 likes0 downloads0 reach2 impact
Weka implementation of FilteredClassifier
135 runs0 likes0 downloads0 reach85 impact
Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL…
135 runs0 likes0 downloads0 reach135 impact
Freund, Y., Mason, L.: The alternating decision tree learning algorithm. In: Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, 124-133, 1999.
135 runs0 likes1 downloads1 reach0 impact
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…
134 runs0 likes0 downloads0 reach1 impact
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…
134 runs0 likes0 downloads0 reach0 impact
Weka implementation of RandomCommittee
134 runs0 likes0 downloads0 reach134 impact
Learner classif.kknn from package(s) !kknn.
134 runs0 likes2 downloads2 reach3 impact
Learner classif.rda from package(s) klaR.
134 runs0 likes1 downloads1 reach0 impact
Weka implementation of FilteredClassifier
133 runs0 likes0 downloads0 reach120 impact
Learner classif.avNNet from package(s) nnet.
133 runs0 likes3 downloads3 reach12 impact
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…
133 runs0 likes0 downloads0 reach0 impact
Learner classif.ranger from package(s) ranger.
132 runs0 likes1 downloads1 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
132 runs0 likes1 downloads1 reach131 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
131 runs0 likes0 downloads0 reach2 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
131 runs0 likes2 downloads2 reach131 impact
Learner classif.neuralnet from package(s) neuralnet.
131 runs0 likes1 downloads1 reach0 impact
Learner classif.glmnet from package(s) !glmnet.
131 runs0 likes1 downloads1 reach0 impact
Learner classif.naiveBayes from package(s) e1071.
131 runs0 likes3 downloads3 reach2 impact
Moa implementation of BLAST
131 runs0 likes3 downloads3 reach57 impact
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…
131 runs0 likes0 downloads0 reach0 impact
Learner classif.ksvm from package(s) kernlab.
129 runs0 likes2 downloads2 reach1 impact
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and…
129 runs0 likes0 downloads0 reach0 impact
Weka implementation of RandomTree
128 runs0 likes3 downloads3 reach100 impact
Moa implementation of MajorityVoteEnsemble
127 runs0 likes0 downloads0 reach0 impact
Jason D. Rennie, Lawrence Shih, Jaime Teevan, David R. Karger: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: ICML, 616-623, 2003.
127 runs0 likes1 downloads1 reach0 impact
Weka implementation of MultiClassClassifierUpdateable
127 runs0 likes1 downloads1 reach125 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.
127 runs0 likes3 downloads3 reach105 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
126 runs0 likes0 downloads0 reach0 impact
Weka implementation of FilteredClassifier
126 runs0 likes0 downloads0 reach61 impact
Learner mlr.classif.naiveBayes.preproc.preproc from package(s) e1071.
126 runs0 likes0 downloads0 reach0 impact
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,…
126 runs0 likes0 downloads0 reach8 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
126 runs0 likes1 downloads1 reach0 impact
Weka implementation of MultiScheme
126 runs0 likes1 downloads1 reach125 impact
Moa implementation of kNN
126 runs0 likes2 downloads2 reach80 impact
Moa implementation of SGD
126 runs0 likes2 downloads2 reach124 impact
Moa implementation of SPegasos
126 runs0 likes2 downloads2 reach124 impact
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
126 runs0 likes3 downloads3 reach95 impact
Weka implementation of DecisionStump
126 runs0 likes3 downloads3 reach97 impact
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
124 runs0 likes3 downloads3 reach94 impact
Learner classif.nnet from package(s) nnet.
123 runs0 likes2 downloads2 reach1 impact
Moa implementation of SGD
122 runs0 likes0 downloads0 reach2 impact
Learner classif.boosting from package(s) adabag, rpart.
121 runs0 likes2 downloads2 reach1 impact
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
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…
120 runs0 likes0 downloads0 reach0 impact
Weka implementation of FilteredClassifier
120 runs0 likes0 downloads0 reach90 impact
Weka implementation of FilteredClassifier
120 runs0 likes0 downloads0 reach60 impact
Moa implementation of kNN
120 runs0 likes0 downloads0 reach0 impact
Moa implementation of SPegasos
120 runs0 likes0 downloads0 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
120 runs0 likes2 downloads2 reach0 impact
N. Littlestone (1988). Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm. Machine Learning. 2:285-318. N. Littlestone (1989). Mistake bounds and logarithmic…
120 runs0 likes2 downloads2 reach6 impact
Learner mlr.classif.kknn.preproc.preproc from package(s) !kknn.
119 runs0 likes0 downloads0 reach0 impact
Automatically created sub-component.
119 runs0 likes0 downloads0 reach64 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
119 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of HIKNN
119 runs0 likes2 downloads2 reach2 impact
Learner classif.multinom from package(s) nnet.
118 runs0 likes2 downloads2 reach1 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
117 runs0 likes1 downloads1 reach0 impact
Weka implementation of AttributeSelectedClassifier
117 runs0 likes0 downloads0 reach0 impact
Moa implementation of WEKAClassifier
116 runs0 likes1 downloads1 reach0 impact
Learner classif.ctree from package(s) party.
116 runs0 likes1 downloads1 reach0 impact
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…
116 runs0 likes0 downloads0 reach0 impact
Weka implementation of FilteredClassifier
116 runs0 likes0 downloads0 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
115 runs0 likes1 downloads1 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
115 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of HwKNN
115 runs0 likes1 downloads1 reach0 impact
Weka implementation of FilteredClassifier
114 runs0 likes1 downloads1 reach11 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
114 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
114 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of KNN
114 runs0 likes2 downloads2 reach0 impact
HubMiner implementation of NHBNN
114 runs0 likes1 downloads1 reach0 impact
Learner classif.cforest from package(s) party.
114 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
113 runs0 likes1 downloads1 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
113 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of HFNN
113 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of DWHFNN
113 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
112 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
112 runs0 likes1 downloads1 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
112 runs0 likes1 downloads1 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
112 runs0 likes1 downloads1 reach0 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
112 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of ANHBNN
112 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of CBWkNN
112 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of NWKNN
112 runs0 likes1 downloads1 reach0 impact
HubMiner implementation of AKNN
112 runs0 likes1 downloads1 reach0 impact
S. Lievens, B. De Baets, K. Cao-Van (2006). A Probabilistic Framework for the Design of Instance-Based Supervised Ranking Algorithms in an Ordinal Setting. Annals of Operations Research.. Kim Cao-Van…
112 runs0 likes2 downloads2 reach101 impact
H. Zhang, L. Jiang, J. Su: Hidden Naive Bayes. In: Twentieth National Conference on Artificial Intelligence, 919-924, 2005.
112 runs0 likes2 downloads2 reach6 impact
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…
112 runs0 likes0 downloads0 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
111 runs0 likes1 downloads1 reach0 impact