Fast Neural Network Ensemble Learning via Negative-Correlation Data Correction

Chan, Z.; Kasabov, N

doi:10.1109/TNN.2005.852859

Chan, Z.; Kasabov, N

Abstract

This letter proposes a new negative correlation (NC) learning method that is both easy to implement and has the advantages that: 1) it requires much lesser communication overhead than the standard NC method and 2) it is applicable to ensembles of heterogenous networks. © 2005 IEEE.

Date

2005

Item Type

Journal Article

Publisher

IEEE

DOI

10.1109/TNN.2005.852859

Rights Statement

©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.