OpenML
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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 CostSensitiveClassifier
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of CostSensitiveClassifier
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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 CostSensitiveClassifier
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Weka implementation of CostSensitiveClassifier
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Weka implementation of AttributeSelectedClassifier
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J.H. Friedman (1999). Stochastic Gradient Boosting.
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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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Moa implementation of HoeffdingTree
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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,…
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Weka implementation of RBFKernel
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Weka implementation of ReplaceMissingValues
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H. Zhang, L. Jiang, J. Su: Hidden Naive Bayes. In: Twentieth National Conference on Artificial Intelligence, 919-924, 2005.
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G.F. Cooper, E. Herskovits (1990). A Bayesian method for constructing Bayesian belief networks from databases. G. Cooper, E. Herskovits (1992). A Bayesian method for the induction of probabilistic…
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of NormalizedPolyKernel
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B. Uestuen, W.J. Melssen, L.M.C. Buydens (2006). Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel. Chemometrics and Intelligent…
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E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ.
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A RapidMiner Operator
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A RapidMiner Operator
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A RapidMiner Operator
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Moa implementation of Perceptron
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Moa implementation of Perceptron
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Learner classif.naiveBayes from package(s) e1071.
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Learner classif.J48 from package(s) RWeka.
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Learner classif.randomForest from package(s) randomForest.
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Learner classif.randomForest from package(s) randomForest.
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Learner classif.rpart from package(s) rpart.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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,…
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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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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Weka implementation of MathParameter
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Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
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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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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,…
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Moa implementation of HoeffdingTree
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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,…
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Learner mlr.classif.rpart from package(s) rpart.
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Learner mlr.classif.randomForest.filtered.oversampled from package(s) mlr, randomForestSRC, randomForest.
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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,…
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Learner mlr.classif.randomForest.filtered from package(s) randomForestSRC, randomForest.
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Learner mlr.classif.rpart from package(s) rpart.
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Learner mlr.classif.rpart.preproc from package(s) rpart.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Learner mlr.classif.rpart.preproc.filtered from package(s) randomForestSRC, rpart.
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Learner mlr.classif.rpart.preproc from package(s) rpart.
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Learner classif.rpart from package(s) rpart.
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Learner mlr.classif.rpart.preproc.filtered from package(s) rpart.
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Weka implementation of LinearRegression
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Learner mlr.classif.logreg.preproc.filtered from package(s) stats.
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Learner mlr.classif.logreg.preproc from package(s) stats.
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Learner mlr.classif.knn from package(s) class.
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Learner mlr.classif.knn.preproc from package(s) class.
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Learner mlr.classif.ctree from package(s) party.
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Learner mlr.classif.rpart from package(s) rpart.
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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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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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,…
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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.
0 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.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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…
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R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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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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J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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Weka implementation of RandomCommittee
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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…
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J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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Learner mlr.classif.kknn.preproc from package(s) !kknn.
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Learner mlr.classif.kknn from package(s) !kknn.
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D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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Learner mlr.classif.kknn.preproc from package(s) !kknn.
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Learner mlr.classif.kknn from package(s) !kknn.
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Learner mlr.classif.naiveBayes from package(s) e1071.
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Weka implementation of MultiSearch
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Weka implementation of MultiSearch
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