Combining Classifiers with Multimethod Approach

摘要

The automatic induction of classifiers from examples is an important technique used in data mining. One of the problems encountered is how to induce a good classifier without overfitting. Although there is a lot of research going on in this field, the research is mainly focused on a specific machine learning method or on a specific combination of those melhods. In this paper a mullimethod approach to combine classifiers is presented that combines advanlages of single melhods and avoids theirs disadvantages at the same lime by applying differenl melhods on the same knowledge model, each of which may contain inherent limitations, with the expectation that the combined multiple melhods may produce better resulls.