title: Fast neural network ensemble learning via negative-correlation data correction.
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.
authors.forename: Zeke S H
authors.initials: ZS
authors.lastname: Chan
authors.forename: Nik
authors.initials: N
authors.lastname: Kasabov
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009716:Numerical Analysis, Computer-Assisted; D013223:Statistics as Topic