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Introduction As a supervised learning algorithm,linear dis-criminant analysis(LDA)is widely used in manyfields,such as face recognition,numerical recogni-tion and information retrieval.The objective ofLDA is to find a project matrix A that maximizesthe ratio of between-class scatter Sbagainst within-class scatter Sw[1].In contrast,an algorithm forunsupervised linear discriminant analysis(ULDA)is presented in this paper.The project matrix A isobtained through maximizing covariance of all … 相似文献
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