Pseudo-inverse LDA Based on QR-decomposition and Support Vectors
Abstract：In order to reduce computational complexity,three kinds of pseudo-inverse linear discriminant analysis methods based on QR-decomposition and support vectors are presented in this paper.Based on Wine and Iris datasets taken from UCI database,experiments compared with pseudo-inverse LDA show that the effectiveness and practicality of the three methods for classification results.
Keywords：pseudo-inverse LDAQR-decompositionsupport vectormisclassification rate
Publication Date：2011-01-01
Online Publishing Date：2026-08-28(First online date of this platform, not the publication date of the document)
Pages：5( 1-5 )