In this paper, we propose a robust and efficient algorithm for generalized orthonormal discriminant vectors (GODV). The major advantage of the proposed method is the use of the ra...
— The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem...
Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Ma...
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...