LLE流形学习的若干问题分析

Analysis of Some Problems in Manifold Learning of LLE

LLE针对非线性降维问题,利用线性重构的局部对称性找出高维数据空间中的非线性结构,并在保持各数据点临近位置关系情况下,把高维空间数据点映射为低维空间对应的数据点。介绍LLE流形学习算法,分析它的优势与不足。

Aiming at the problem of nonlinear dimensionality reduction, presents local linear embedding （LLE）algorithm. The nonlinear structure in high dimensional data space is exploited with the local symmetries of linear reconstructions. Maps the data points in high dimensional space into corresponding data points in lower dimensional space under preserving distance between data points. Introduces a manifold learning algorithm of LLE, summarizes some problems of LLE and its research status, and discusses the prospect of LLE.