Exploring the structure of supervised data by Discriminant Isometric Mapping

摘要

In this paper, we investigated nonlinear dimensionality reduction (NLDR) for supervised learning and introduced a novel algorithm named supervised isometric mapping (SIsomap) which was based on a combination of two well-known methods: isomap and fuzzy linear discriminant analysis (LDA).