Multiple Classifier Systems for Adversarial Classification Tasks
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
An ensemble dependence measure
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
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Stochastic Discrimination is a machine learning algorithm with strong theoretical underpinnings and good published results on UCI datasets. However, it has not been popular amongst practitioners. We look at some of the issues involved in its use, propose the Out-of-Bootstrap error estimator as a means of tuning Stochastic Discrimination's and other classifiers' performance and contrast Stochastic Discrimination's utility with that of a related classification technique of Random Forests.