David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
4 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2 runs0 likes2 downloads2 reach1 impact
Weka implementation of BayesNet
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
3 runs0 likes3 downloads3 reach2 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
1 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2 runs0 likes1 downloads1 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of InputMappedClassifier
0 runs0 likes0 downloads0 reach0 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…
4 runs0 likes2 downloads2 reach3 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,…
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Weka implementation of PolyKernel
0 runs0 likes0 downloads0 reach0 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.
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S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.
0 runs0 likes0 downloads0 reach0 impact
Y. Freund, R. E. Schapire: Large margin classification using the perceptron algorithm. In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.
0 runs0 likes0 downloads0 reach0 impact
Y. Freund, R. E. Schapire: Large margin classification using the perceptron algorithm. In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.
0 runs0 likes0 downloads0 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
1 runs0 likes1 downloads1 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of RandomTree
0 runs0 likes0 downloads0 reach0 impact
Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.
1 runs0 likes1 downloads1 reach0 impact
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy: Improvements to the SMO Algorithm for SVM Regression. In: IEEE Transactions on Neural Networks, 1999. A.J. Smola, B. Schoelkopf (1998). A…
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S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy: Improvements to the SMO Algorithm for SVM Regression. In: IEEE Transactions on Neural Networks, 1999. S.K. Shevade, S.S. Keerthi, C.…
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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…
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.
1 runs0 likes1 downloads1 reach0 impact
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
1 runs0 likes1 downloads1 reach0 impact
Weka implementation of MultiClassClassifier
1 runs0 likes1 downloads1 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
1 runs0 likes1 downloads1 reach0 impact
J.H. Friedman (1999). Stochastic Gradient Boosting.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
An implementation of the evaluation measure "usercpu_time_millis"
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For survival analysis
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
10 runs0 likes4 downloads4 reach6 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
3 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
Weka implementation of AttributeSelectedClassifier
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
2 runs0 likes1 downloads1 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of AttributeSelectedClassifier
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 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…
1 runs0 likes1 downloads1 reach0 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…
1 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2 runs0 likes1 downloads1 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of REPTree
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
4 runs0 likes2 downloads2 reach3 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
7 runs0 likes5 downloads5 reach6 impact
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
2 runs0 likes2 downloads2 reach1 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of BayesNet
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of HillClimber
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of BayesNet
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 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…
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
2 runs0 likes2 downloads2 reach1 impact
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
0 runs0 likes0 downloads0 reach0 impact
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
1 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.
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of BayesNet
0 runs0 likes0 downloads0 reach0 impact
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
0 runs0 likes0 downloads0 reach0 impact