基于确信因子的有效关联规则挖掘

通过对现有的关联规则算法分析与研究发现,生成的关联规则具有相大的冗余性,且可能是无趣的,甚至是虚假的,为此人们主要提出了兴趣度作为有效规则评判标准。该文在先前研究的基础上,以确信因子为基础,提出确信度来使规则的有效性判断更加客观、合理。同时在算法中引入规则取舍,提高了挖掘有效规则的效率。

Mining Efficient Association Rules Based on CF Gene

By analyzing and studying the most current algorithms about mining association rules,people find that gener-ated association rules are quite redundant ,and many rules,which possess high support and confidence are uninteresting,and even are false.Therefore,interest measurer is introduced to enchance the validity of association rules.Based on the previous work,this paper proposes CF measure and put s it as threshold to mine valuable rules.At the same time ,this paper establishes a theory architecture to accept or reject or reserve synchronously a pair of rules by analyzing CF gene,and introduces it to the algorithms.Finally,this algorithms is evaluated and is more efficient through experiments.