A New DC Algorithm for Sparse Optimal Scoring Problem

Linear discriminant analysis (LDA) has attracted many attentions as a classical tool for both classification and dimensionality reduction. Classical LDA performs quite well in simple and low dimensional setting while it is not suitable for small sample size data (SSS). Feature selection is an effect...

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Bibliographic Details

Published in:	IEEE access Vol. 8; pp. 53962 - 53971
Main Authors:	Li, Guo-Quan, Duan, Xu-Xiang, Wu, Chang-Zhi
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Approximation algorithms Continuity (mathematics) Convergence Convex functions dc algorithm Dimensionality reduction Discriminant analysis Exact solutions Feature extraction Linear discriminant analysis Optimization Regularization sparse optimal scoring ℓ₀-norm
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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