公开(公告)号：US10810490B2

公开(公告)日：2020-10-20

申请号：US15018656

申请日：2016-02-08

Applicant: Beijing University of Technology

Inventor： Lijuan Duan ,  Bin Yuan ,  Song Cui ,  Jun Miao ,  Junfa Liu

IPC: G06N3/08

Abstract: The present invention relates to a clustering method based on iterations of neural networks, which comprises the following steps: step 1, initializing parameters of an extreme learning machine; step 2, randomly choosing samples of which number is equal to the number of clusters, each sample representing one cluster, forming an initial exemplar set and training the extreme learning machine; step 3, using current extreme learning machine to cluster samples, which generates a clustering result; step 4, choosing multiple samples from each cluster as exemplars for the cluster according to a rule; step 5, retraining the extreme learning machine by using the exemplars for each cluster obtained from step 4; and step 6, going back to step 3 to do iteration, otherwise obtaining and outputting clustering result until clustering result is steady or a maximal limit of the number of iterations is reached. The present invention resolves problems that how to realize clustering of high dimensional and nonlinear data space and that the prior art consumes a larger memory or need longer running time.