Ontology highlight
ABSTRACT:
SUBMITTER: Ni S
PROVIDER: S-EPMC4498733 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Ni Shengqiao S Lv Jiancheng J Cheng Zhehao Z Li Mao M
PloS one 20150710 7
This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, an ...[more]