OpenML
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…
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Weka implementation of CostSensitiveClassifier
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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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M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.
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Weka implementation of BestFirst
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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 AttributeSelectedClassifier
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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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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…
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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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J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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J.H. Friedman (1999). Stochastic Gradient Boosting.
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Weka implementation of CostSensitiveClassifier
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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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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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R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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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Ron Kohavi, George H. John (1997). Wrappers for feature subset selection. Artificial Intelligence. 97(1-2):273-324.
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Weka implementation of CostSensitiveClassifier
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David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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Weka implementation of PolyKernel
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Weka implementation of CostSensitiveClassifier
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Weka implementation of RandomCommittee
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Weka implementation of AttributeSelectedClassifier
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Ron Kohavi, George H. John (1997). Wrappers for feature subset selection. Artificial Intelligence. 97(1-2):273-324.
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Weka implementation of CostSensitiveClassifier
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Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive. In: Fifth International Conference on Knowledge Discovery and Data Mining, 155-164, 1999.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Weka implementation of CostSensitiveClassifier
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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 RandomCommittee
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Weka implementation of CostSensitiveClassifier
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Weka implementation of PrincipalComponents
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Weka implementation of Ranker
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Weka implementation of CostSensitiveClassifier
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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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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 GreedyStepwise
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Weka implementation of CostSensitiveClassifier
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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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Kenji Kira, Larry A. Rendell: A Practical Approach to Feature Selection. In: Ninth International Workshop on Machine Learning, 249-256, 1992. Igor Kononenko: Estimating Attributes: Analysis and…
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Weka implementation of CostSensitiveClassifier
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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 AttributeSelectedClassifier
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Weka implementation of InfoGainAttributeEval
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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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Weka implementation of GainRatioAttributeEval
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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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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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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Weka implementation of CostSensitiveClassifier
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Weka implementation of RandomCommittee
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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 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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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…
9 runs0 likes0 downloads0 reach9 impact
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.
0 runs0 likes0 downloads0 reach0 impact
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.
0 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,…
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.
0 runs0 likes0 downloads0 reach0 impact