Introduction - If you have any usage issues, please Google them yourself
Classic pattern recognition algorithm, which is introduced in 1996 by Belhumeur pattern recognition and artificial intelligence. The basic idea of discriminant analysis of high-dimensional pattern is projected onto the sample optimal discriminant vector space, in order to achieve the classification of information extraction and compression feature space dimension effect, the projected sample assurance model in the new sub-space of the largest class the minimum distance and within-class distance, mode has the best separability in the space. Therefore, it is an effective method of feature extraction. Between the use of this method enables projection mode sample class scatter matrix largest and the smallest in the class scatter matrix simultaneously. That is, it can ensure that the samples have a minimum projection mode classes and maximum distance between the distance class, that has the best model separability in the space in the new space.