Research and development of attribute reduction algorithm based on rough set

Attribute reduction is a form of the data reduction, usually as a preprocessing step in data mining. Its job is to maintain the knowledge base under the premise of the same classification ability to remove irrelevant and redundant attributes properties, thereby reducing the search space and improve efficiency. In recent years, attribute reduction has become the focus and hot spot of research in the field of Rough Set. This paper reviews the current domestic and foreign attribute reduction algorithm on a number of the latest research advances, focusing on the mainstream of attribute reduction methods and cutting-edge progress summary and analysis. And it concludes with a brief discussion of the future direction of research and development.