The Improvement and Application of the Fuzzy K-Prototypes Algorithm
Lilin Fan · 2009
Fuzzy K-prototypes is a very efficient algorithm for processing large scale mixed data set, but the selection of initial clustering center has an important impact on the clustering effect of algorithm. FKP algorithm is improved by using genetic algorithm in this paper. Seeking the initial clustering center for fuzzy K-prototypes algorithm by using genetic algorithm overcomes the shortcoming effectively, which has been applied to customer data segmentation of automobile industry collaborative platform. It is proved that the improved effect is obviously.