Supervised locality preserving projection based on class information
Jing Wang · Journal of Computer Applications · 2012
Locality Preserving Projection(LPP) is an approximation of Laplacian Eigenmap(LE),but it is an unsupervised method,and does not take advantage of the existing classification information to improve the classification efficiency.Therefore,a supervised locality preserving projection named SLPP-LI method was proposed based on class information.In the study of projection matrix,SLPP-LI took advantage of the comprehensive utilization of the geometrical structure of the manifold and the class information of the existing train set,SLPP-LI can effectively take advantage of the known low dimensional information by adjusting the control parameters and obtain the low-dimensional models of high dimensional data by directly solving the linear equation.The comparative experiments with several face databases and handwritten digital databases show,SLPP-LI is neither sensitive to the original dimension of high dimension data,nor the number of the training data.For the same kind of problems,SLPP-LI has higher recognition rate compared with PCA,LPP,OLPP and SLPP,and it can effectively deal with the classification issues.