关键词: 差异性, 集成学习, 分类器, 聚类

Abstract: Aiming at diversity being a necessary condition of the ensemble learning，this paper studies the method for improving diversity of the neural networks ensemble based on k-means clustering technique.This paper proposes a selecting approach that is first to train many classifiers through training set with neural network algorithm，and uses the result by the classifiers from validation set for clustering.And then this paper uses the k-means algorithm to cluster the data set from the result and selects a classifier model from every cluster to make up of the membership of the ensemble learning.At last，this paper studies the performance of ensemble method by using vote method and compare performance with bagging and adaboost methods.

Key words: diversity, ensemble learning, classifier, clustering