Application of Incremental Associative Classification Method in Malware Detection
Zhixue Han · Jisuanji gongcheng · 2009
Traditional associative rule mining algorithm is mostly based on the support-confidence framework,which disable the in-depth study of frequent items for time and space limitations.There is few study of associative classification incremental learning currently.This paper presents a new incremental associative classification method,which can solve the incremental learning problems of data with class attribute,and realize the fast extraction and maintenance of associative rule with limited time and space when the data is updating frequently.Experimental results show that this method can quickly and effectively maintain and update the classification rules,which avoid re-learning the history samples and ensure the predictability of the classification model.