Projection pursuit clustering modeling applying multi-agent genetic algorithm and positive research
Lou Wen-ga · Computer Engineering and Applications Journal · 2013
Multi-agent Genetic Algorithm(MGA)is applied to effectively and successfully optimize the optimal projection vector in the Projection Pursuit Clustering(PPC)model.Two different normalization methods,without changing the evolution process,for projection vector get the same results for three cases with various amounts of samples.The two different Maximum and Minimum Normalization Methods(MMNMs)for evaluation indexes yield opposite number of projection vector coefficients.The difference between the projected values of the same sample with two different MMNMs is constant.The PPC model is thus suitable to exploratory research and confirmatory analysis.PPC model is mainly applied to large sample situation and gets properly reliable and effective results.The correlation between variables will influence PPC model's effectiveness and rational.