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Indexed by:期刊论文

Date of Publication:2015-09-01

Journal:Journal of Information and Computational Science

Included Journals:EI、Scopus

Volume:12

Issue:13

Page Number:4951-4958

ISSN No.:15487741

Abstract:Original ELM-AE algorithm combines Extreme Learning Machine (ELM) with Auto Encoder (AE) to map data to a nonlinear high-dimensional space. This procedure can extract better sample characteristics when solving unsupervised clustering problems. ELM-AE adopts a solution procedure which is similar to ELM to improve the solution speed. However, ELM-AE has some problems. The solution of the system is not stable because of the random input-layer weights. Meanwhile, if the number of hidden layers is small, model fitting effect will be significantly reduced. To solve the above problems, we propose a Robust ELM-AE (RELM-AE) clustering algorithm. This method trains Restricted Boltzmann Machine (RBM) to get stable input-layer weights, and then minimizes the output error to obtain the output-layer weights. Compared with the original model of ELM-AE, this method achieves more stable and accurate results, which makes it more suitable for solving unsupervised clustering problems. ?, 2015, Journal of Information and Computational Science. All right reserved.