Clustering Algorithm based on Immunological Partheno Genetic and Fuzzy C-Means

摘要

Clustering algorithm is an important way of the data mining.This paper analyzes the lack of FCM algorithm and genetic clustering algorithm.Propose a hybrid clustering algorithm based on immune single genetic and fuzzy C-means.This algorithm not only overcomes the local optimal problem of FCM because of the inappropriate choice of the initial value, but also overcomes the contradictions between the search speed and clustering accuracy of the general genetic clustering algorithm.Experiments show that the algorithm is effective.