Abstract: Genetic algorithms are an important data mining classification mining algorithms.The simple genetic algorithm has great randomness，higher error rate.It is difficult to meet the needs of data mining.To this end，this paper presents a genetic algorithm and the Apriori-based classification mining algorithms——GAA.From the code design，fitness function，genetic operators to discuss the design and analysis，an instance is adopted to complete the application.The results show that the algorithm in few algebraic cases，can effectively improve the classification accuracy，and has a certain practical value.

Key words: data mining, genetic algorithm, association rules, classification

摘要： 遗传算法是数据挖掘中一种重要的分类挖掘算法，但简单的遗传算法具有很大的随机性，出错率较高，难以满足数据挖掘的需要。为此，提出一种基于遗传算法和Apriori的分类挖掘算法——GAA。从编码设计、适应度函数、遗传算子的设计方面进行讨论和分析，结合一个具体实例进行应用，结果表明算法在代数较少情况下，可有效提高分类的准确性，具有一定的应用价值。

关键词: 数据挖掘, 遗传算法, 关联规则, 分类