一种基于混合算法的分类规则挖掘

An Method of Classification Rule Discovery Based on a Hybrid Algorithm

为了高效地从数据库中挖掘分类规则,提出了一种将粒子群优化算法和遗传算法相结合的新算法。该算法的核心思想为:对规则的前件进行二进制编码,适应度函数的计算由分类规则的准确率和简洁度构成。并将此算法分别与遗传算法和粒子群算法进行了实验比较,结果表明该算法不仅具有更快的收敛速度,而且获得了更高的预测准确率。

To efficiently mine the classification rule from database,a novel hybrid classification algorithm based on particle swarm optimization(PSO)and genetic algorithm(GA) was proposed.The core idea of the proposed algorithm is as follows.The rule antecedent is encoded as binary chromosome;The fitness function is calculated according to accuracy and simplicity of rules.The experimental results show that the proposed classification algorithm not only has faster convergence speed,but also can achieve higher classification accuracy compared with other classification algorithms.