A Tangent Distance Preserving Dimensionality Reduction Algorithm

Autor:	Zhao, Xu, Jiang, Zongli
Rok vydání:	2019
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	This paper considers the problem of nonlinear dimensionality reduction. Unlike existing methods, such as LLE, ISOMAP, which attempt to unfold the true manifold in the low dimensional space, our algorithm tries to preserve the nonlinear structure of the manifold, and shows how the manifold is folded in the high dimensional space. We call this method Tangent Distance Preserving Mapping (TDPM). TDPM uses tangent distance instead of geodesic distance, and then applies MDS to the tangent distance matrix to map the manifold into a low dimensional space in which we can get its nonlinear structure. Comment: Signal and Image Processing (SIP 2008)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1902.05373 Zobrazit plný text záznamu View this record from Arxiv