Attribute Reduction in Rough Set Theory.

      Аннотация: The fast growth of technology and necessity of using computerized data lead the human beings to search and discover new methods in data mining vast area. This book introduces the new approach of meta-heuristic algorithms in rough set attribute reduction in order to avoid the curse of dimensionality and finding the reduce subset of datasets. Meanwhile, estimation the accuracy of the model by classification task is accomplished. The proposed method in this book proves that Reheat-SA is a powerful method for large scale combinational optimization.

Ключевые слова: Data Mining, Rough Set Theory, REHEAT SIMULATED ANNEALING, Attribure Reduction