基于基因表达式编程的自动聚类方法

为了解决聚类算法不能自动聚类的问题,提出并实现了自动聚类算法GEP-Cluster算法。主要工作包括:1)研究了基于GEP进化的最优簇划分;2)提出了自动合并簇算法Auto Merge Cluster Algorithm;3)实现了不需预知簇个数的聚类;4)在合成数据集上的实验表明,采用GEP-Cluster算法在未知簇划分信息的情况下可对数据集自动进行聚类分析,聚类成功率达到96%。

An Auto clustering Algorithm Based on Gene Expression Programming

Many clustering algorithms have to need a number of clusters before clustering.In order to tackle this problem,a novel GEP-Cluster(Gene Expression Programming-clustering) algorithm was proposed.The main contributions include: 1) proposing the GEP-Cluster algorithm to find the best clustering via GEP evolution,2) proposing AMCA algorithm to auto merge cluster,3) finding the best clustering without any priori knowledge by the GEP-Cluster algorithm.Extensive experiments showed that GEP-Cluster algorithm is effective in clustering without any domain knowledge,and the average clustering accuracy is almost 96%.