The Research of Key Data Classification Optimal Mining Methods for Massive Data

Abstract

The data classification is an important issue in massive data classification. This paper proposes an inter-cell classification algorithm based on phase recombination neighbor points convergence which analyzes the convergence value weights of inter-cell characteristic points and filter the interferences of the minority local optimal characteristic points. The proposed algorithm can promote the convergence of the inter-cell classification data neighbor points. The simulation experiments testify the models by three types of actually collected data sets which illustrate the models have better classification performance.