A Study on Classification Method of Discrete Data Basic on Improved Association Rules

Abstract

A large amount of data is involved in the processing of discrete data. As there is a large quantity of redundancy discrete data in mass data, it causes the error of discrete data association and reduced classification effect. To solve this problem, we brought forward the classification method of discrete data to improve associated mining algorithm. Before establishing association rule, we performed secondary validation of information which may contain redundancy data to lower down the probability of error in discrete data association, thus the possibility of false classification of data, and remove the defect of traditional method. As proved by simulation experiment, this improved algorithm is able to largely raise the preciseness of discrete data association and achieve better effect.