%0 Journal Article
%T Associative classification based on hybrid strategy<br>基于混合策略的关联分类方法
%A LI Xue-ming
%A FU Meng
%A LI Bin-fei
%A <br>李学明
%A 付　萌
%A 李宾飞
%J 计算机应用研究
%D 2013
%I 
%X The existing explicit learning method of associative classification can't solve small disjunction problem and the lazy method's classification efficiency is low. According to the deficiency of the two approaches, this paper proposed an improved algorithm, associative classification based on hybrid strategy. The algorithm could be summarized as follows. Firstly, it judged whether the test sample met the classifier characters of the explicit learning mode, then used the explicit learning method to classify the test sample which met the classifier characters and used the Lazy method to classify the test sample which didn't meet the classifier characters. Finally, it combined the classification results of the two types of methods to get the final classification results. The experiments compared this method with the traditional associative classification approaches. Results show that the method is more effective in terms of classification accuracy and execution efficiency.
%K hybrid strategy
%K associative classification approach
%K explicit learning method
%K Lazy method<br>混合策略
%K 关联分类方法
%K 显式学习方法
%K Lazy方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=57319E4289F4438F7EF9D3526CD7C646&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=94655B9881133A28&eid=0EE24608F5763811&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=14