高选票例外模式挖掘研究与实现

Study and Implementation on High-voting Exceptional Pattern Mining

例外模式挖掘是数据挖掘的一项重要内容。提出一种新的多数据库中的例外模式——高选票例外模式,并提出一种挖掘方法,局部分析每一个数据库得到局部模式,再将局部模式进行聚类,在每个类中先找到高选票模式,再根据方差的性质最终得到例外模式;并用实验验证了该方法的正确性和有效性。

Mining exceptions is an important topic in data mining. This paper proposes a new exceptional pattern and an approach of mining new exceptions in multi-database . Through analysis of every database locally to obtain local patterns and then cluster them . Find high-voting patterns in every class, we can obtain exceptions according to square deviation. We also evaluate our algorithm experimentally . It is validated that our algorithm is effective and efficient.