Rough Set Based Ensemble Classifier

Abstract

Combining the results of a number of individually trained classification systems to obtain a more accurate classifier is a widely used technique in pattern recognition. In [1], we introduced a Rough Set Meta classifier (RSM) to classify web pages. It tries to solve the problems of representing less redundant ensemble of classifiers and making reasonable decision from the predictions of ensemble classifiers, using rough set attribute reduction and rule generation methods on a granular meta data generated by base classifiers from input data.