A deterministic approach to regularized linear discriminant analysis

被引：32
|
作者：
Sharma, Alok [1 ,2 ]
Paliwal, Kuldip K. [1 ]
机构：
[1] Griffith Univ, Sch Engn, Brisbane, Qld 4111, Australia
[2] Univ S Pacific, Sch Phys & Engn, Suva, Fiji
来源：
NEUROCOMPUTING | 2015年 / 151卷
关键词：
Linear discriminant analysis (LDA); Regularized LDA; Deterministic approach; Cross-validation; Classification; SMALL SAMPLE-SIZE; FACE RECOGNITION; DIRECT LDA; FAST IMPLEMENTATION; NULL SPACE; CLASSIFICATION; PREDICTION; ALGORITHM; CANCER; DISCOVERY;
D O I：
10.1016/j.neucom.2014.09.051
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The regularized linear discriminant analysis (RLDA) technique is one of the popular methods for dimensionality reduction used for small sample size problems. In this technique, regularization parameter is conventionally computed using a cross-validation procedure. In this paper, we propose a deterministic way of computing the regularization parameter in RLDA for small sample size problem. The computational cost of the proposed deterministic RLDA is significantly less than the cross-validation based RLDA technique. The deterministic RLDA technique is also compared with other popular techniques on a number of datasets and favorable results are obtained. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：207 / 214
页数：8
相关论文
共 50 条
  • [1] Regularized orthogonal linear discriminant analysis
    Ching, Wai-Ki
    Chu, Delin
    Liao, Li-Zhi
    Wang, Xiaoyan
    [J]. PATTERN RECOGNITION, 2012, 45 (07) : 2719 - 2732
  • [2] Regularized complete linear discriminant analysis
    Yang, Wuyi
    Wu, Houyuan
    [J]. NEUROCOMPUTING, 2014, 137 : 185 - 191
  • [3] On the dimension effect of regularized linear discriminant analysis
    Wang, Cheng
    Jiang, Binyan
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2018, 12 (02): : 2709 - 2742
  • [4] Comparison of regularized discriminant analysis, linear discriminant analysis and quadratic discriminant analysis, applied to NIR data
    Wu, W
    Mallet, Y
    Walczak, B
    Penninckx, W
    Massart, DL
    Heuerding, S
    Erni, F
    [J]. ANALYTICA CHIMICA ACTA, 1996, 329 (03) : 257 - 265
  • [5] Robust Face Recognition Method Based on Kernel Regularized Relevance Weighted Discriminant Analysis and Deterministic Approach
    Di Wu
    [J]. Sensing and Imaging, 2019, 20
  • [6] Robust Face Recognition Method Based on Kernel Regularized Relevance Weighted Discriminant Analysis and Deterministic Approach
    Wu, Di
    [J]. SENSING AND IMAGING, 2019, 20 (01):
  • [7] Graph regularized linear discriminant analysis and its generalization
    Huang, Sheng
    Yang, Dan
    Zhou, Jia
    Zhang, Xiaohong
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2015, 18 (03) : 639 - 650
  • [8] Orthogonal Regularized Linear Discriminant Analysis for Face Recognition
    Li, Feng
    [J]. PROCEEDINGS OF 2012 IEEE 11TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP) VOLS 1-3, 2012, : 1213 - 1216
  • [9] Regularized linear discriminant analysis and its application in microarrays
    Guo, Yaqian
    Hastie, Trevor
    Tibshirani, Robert
    [J]. BIOSTATISTICS, 2007, 8 (01) : 86 - 100
  • [10] Classification of Hyperspectral Images With Regularized Linear Discriminant Analysis
    Bandos, Tatyana V.
    Bruzzone, Lorenzo
    Camps-Valls, Gustavo
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (03): : 862 - 873
12345