Research on data mining algorithm based on matrix

As large-scale data processing and data mining become more and more important, knowledge acquisition has become a more and more popular research topic. This paper discusses the method of combining rough set theory with binary discernible matrix to reduce the knowledge of decision tables, analyzes the existing attribute reduction algorithms and rough set models related to complete and incomplete decision tables, gives the concept of generalized binary discernible matrix suitable for complete and incomplete decision tables, and gives an algorithm for attribute reduction and rule extraction based on generalized binary discernible matrix.