Overview of manifold learning
XU Rong,JIANG Feng, YAO Hong-xun(School of Computer Science and Technology, Harbin Institute of Technology,Harbin 150001,China)
As a new unsupervised learning method, manifold learning is capturing increasing interests of researchers in the field of machine learning and cognitive sciences. To understand manifold learning better, the topology concept of manifold learning was presented firstly, and then its development history was traced. Based on different representations of manifold, several major algorithms were introduced, whose advantages and defects were pointed out respectively. After that, two kinds of typical applications of Isomap and LLE were indicated. The results show that compared with traditional linear method, manifold learning can discover the intrinsic dimensions of nonlinear high-dimensional data effectively, helping researchers to reduce dimensionality and analyze data better. Finally the prospect of manifold learning was discussed, so as to extend the application area of manifold learning.