14.1.4.8 Discriminant Analysis

Discriminant Function Analysis,
StatSoftElectronic Text, 2003.
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On the problem of bias in error rate estimation for discriminant analysis,
PR(3), No. 3, October 1971, pp. 217-223.
Elsevier DOI 0309
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Chhikara, R.S., Odell, P.L.,
Discriminant analysis using certain normed exponential densities with emphasis on remote sensing application,
PR(5), No. 3, September 1973, pp. 259-272.
Elsevier DOI 0309
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Foley, D.H., and Sammon, Jr., J.W.,
An optimal set of discriminant vectors,
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See also nonlinear mapping for data structure analysis, A. BibRef 7503

McLachlan, G.J.,
Further results on the effect of intraclass correlation among training samples in discriminant analysis,
PR(8), No. 4, October 1976, pp. 273-275.
Elsevier DOI 0309
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McLachlan, G.J.,
Discriminant Analysis and Statistical Pattern Recognition,
John Wileyand Sons, New York, 1992. General reference book. BibRef 9200

Pudil, P.[Pavel], Bláha, S.[Svatopluk],
Evaluation of the effectiveness of features selected by discriminant analysis methods,
PR(14), No. 1-6, 1981, pp. 81-85.
Elsevier DOI 0309
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Somol, P.[Petr], Grim, J.[Jirí], Filip, J.[Jirí], Pudil, P.[Pavel],
On Stopping Rules in Dependency-Aware Feature Ranking,
CIARP13(I:286-293).
Springer DOI 1311
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Lawoko, C.R.O., McLachlan, G.J.,
Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function,
PR(16), No. 1, 1983, pp. 119-121.
Elsevier DOI 0309
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Bobrowski, L., Niemiro, W.,
A method of synthesis of linear discriminant function in the case of nonseparability,
PR(17), No. 2, 1984, pp. 205-210.
Elsevier DOI 0309
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Okada, T.[Toshiniko], Tomita, S.[Shingo],
An optimal orthonormal system for discriminant analysis,
PR(18), No. 2, 1985, pp. 139-144.
Elsevier DOI 0309
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Tutz, G.E.[Gerhard E.],
Smoothed additive estimators for non-error rates in multiple discriminant analysis,
PR(18), No. 2, 1985, pp. 151-159.
Elsevier DOI 0309
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Krishnan, T., Nandy, S.C.,
Discriminant analysis with a stochastic supervisor,
PR(20), No. 4, 1987, pp. 379-384.
Elsevier DOI 0309
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Krishnan, T., Nandy, S.C.,
Efficiency of logistic-normal stochastic supervision,
PR(23), No. 11, 1990, pp. 1275-1279.
Elsevier DOI 0401
logarithm of odds ratio of the supervisor classification has a normal distribution and is independent of the feature vector. BibRef

Katre, U.A., Krishnan, T.,
Pattern recognition with an imperfect supervisor,
PR(22), No. 4, 1989, pp. 423-431.
Elsevier DOI 0309
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Titterington, D.M.,
An alternative stochastic supervisor in discriminant analysis,
PR(22), No. 1, 1989, pp. 91-95.
Elsevier DOI 0309
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Krusinska, E.[Ewa],
Two step semi-optimal branch and bound algorithm for feature selection in mixed variable discrimination,
PR(22), No. 4, 1989, pp. 455-459.
Elsevier DOI 0309
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Wyman, F.J.[Frank J.], Young, D.M.[Dean M.], Turner, D.W.[Danny W.],
A comparison of asymptotic error rate expansions for the sample linear discriminant function,
PR(23), No. 7, 1990, pp. 775-783.
Elsevier DOI 0401
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Flasinski, M.[Mariusz], Lewicki, G.[Grzegorz],
The convergent method of constructing polynomial discriminant functions for pattern recognition,
PR(24), No. 10, 1991, pp. 1009-1015.
Elsevier DOI 0401
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Cox, T.F.[Trevor F.], Ferry, G.[Gillian],
Discriminant analysis using non-metric multidimensional scaling,
PR(26), No. 1, January 1993, pp. 145-153.
Elsevier DOI 0401
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Brasher, J.D., Kinser, J.M.,
Fractional-power synthetic discriminant functions,
PR(27), No. 4, April 1994, pp. 577-585.
Elsevier DOI 0401
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Lovell, D.R., Dance, C.R., Niranjan, M., Prager, R.W., Dalton, K.J., Derom, R.,
Feature-Selection Using Expected Attainable Discrimination,
PRL(19), No. 5-6, April 1998, pp. 393-402. 9808
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Saito, N.[Naoki], Coifman, R.R.[Ronald R.], Geshwind, F.B.[Frank B.], Warner, F.[Fred],
Discriminant feature extraction using empirical probability density estimation and a local basis library,
PR(35), No. 12, December 2002, pp. 2841-2852.
Elsevier DOI 0209
BibRef

Jing, X.Y.[Xiao-Yuan], Zhang, D.[David], Jin, Z.[Zhong],
Improvements on the Uncorrelated Optimal Discriminant Vectors,
PR(36), No. 8, August 2003, pp. 1921-1923.
Elsevier DOI 0304

See also Face recognition based on a group decision-making combination approach. BibRef

Xu, Y.[Yong], Yang, J.Y.[Jing-Yu], Jin, Z.[Zhong],
Theory analysis on FSLDA and ULDA,
PR(36), No. 12, December 2003, pp. 3031-3033.
Elsevier DOI 0310
Uncorrelated linear discriminant analysis.
See also Face recognition based on the uncorrelated discriminant transformation. BibRef

Jing, X.Y.[Xiao-Yuan], Zhang, D.[David], Jin, Z.[Zhong],
UODV: Improved Algorithm and Generalized Theory,
PR(36), No. 11, November 2003, pp. 2593-2602.
Elsevier DOI 0309
BibRef

Ma, J.S.[Jun-Shui], Theiler, J.[James], Perkins, S.[Simon],
Two realizations of a general feature extraction framework,
PR(37), No. 5, May 2004, pp. 875-887.
Elsevier DOI 0405
Extension of conventional linear discriminant analysis. Kernel feature extraction, mean-norm feature extraction. BibRef

Chen, S.C.[Song-Can], Yang, X.B.[Xu-Bing],
Alternative linear discriminant classifier,
PR(37), No. 7, July 2004, pp. 1545-1547.
Elsevier DOI 0405
BibRef

Park, C.H.[Cheong Hee], Park, H.S.[Hae-Sun],
A comparison of generalized linear discriminant analysis algorithms,
PR(41), No. 3, March 2008, pp. 1083-1097.
Elsevier DOI 0711
Dimension reduction; Feature extraction; Generalized linear discriminant analysis; Kernel methods; Nonlinear discriminant analysis; Undersampled problems
See also Fingerprint classification using fast Fourier transform and nonlinear discriminant analysis. BibRef

Ye, J.P.[Jie-Ping], Janardan, R.[Ravi], Park, C.H.[Cheong Hee], Park, H.S.[Hae-Sun],
An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems,
PAMI(26), No. 8, August 2004, pp. 982-994.
IEEE Abstract. 0407
Extend LDA by using pseudoinverse with matricies are singular. BibRef

Howland, P.[Peg], Park, H.S.[Hae-Sun],
Generalizing Discriminant Analysis Using the Generalized Singular Value Decomposition,
PAMI(26), No. 8, August 2004, pp. 995-1006.
IEEE Abstract. 0407
Use GSVD to deal with singular matricies. BibRef

Howland, P.[Peg], Wang, J.L.[Jian-Lin], Park, H.S.[Hae-Sun],
Solving the small sample size problem in face recognition using generalized discriminant analysis,
PR(39), No. 2, February 2006, pp. 277-287.
Elsevier DOI 0512
BibRef

Kim, H.[Hyunsoo], Drake, B.L.[Barry L.], Park, H.S.[Hae-Sun],
Multiclass classifiers based on dimension reduction with generalized LDA,
PR(40), No. 11, November 2007, pp. 2939-2945.
Elsevier DOI 0707
Multiclass classifier; Generalized linear discriminant analysis (LDA); Generalized singular value decomposition (GSVD); Dimension reduction; Undersampled problems BibRef

Li, Q.[Qi], Kambhamettu, C.[Chandra], Ye, J.P.[Jie-Ping],
Integrating Spatial and Discriminant Strength for Feature Selection and Linear Dimensionality Reduction,
BP06(21).
IEEE DOI 0609
BibRef

Liang, Z.Z.[Zhi-Zheng], Shi, P.F.[Peng-Fei],
Uncorrelated discriminant vectors using a kernel method,
PR(38), No. 2, February 2005, pp. 307-310.
Elsevier DOI 0411
Extend approach of:
See also Face recognition based on the uncorrelated discriminant transformation. for character recognition. BibRef

Liang, Z.Z.[Zhi-Zheng], Shi, P.F.[Peng-Fei],
Kernel direct discriminant analysis and its theoretical foundation,
PR(38), No. 3, March 2005, pp. 445-447.
Elsevier DOI 0412
BibRef

Liang, Z.Z.[Zhi-Zheng], Li, Y.F.[You-Fu], Shi, P.F.[Peng-Fei],
A note on two-dimensional linear discriminant analysis,
PRL(29), No. 16, 1 December 2008, pp. 2122-2128.
Elsevier DOI 0811
Feature extraction; Linear discriminant analysis; 2DLDA; Discriminant power; Distance measure BibRef

Hua, J.P.[Jian-Ping], Xiong, Z.X.[Zi-Xiang], Dougherty, E.R.[Edward R.],
Determination of the optimal number of features for quadratic discriminant analysis via the normal approximation to the discriminant distribution,
PR(38), No. 3, March 2005, pp. 403-421.
Elsevier DOI 0412
BibRef

Dougherty, E.R.[Edward R.], Hua, J.P.[Jiang-Ping], Xiong, Z.X.[Zi-Xiang], Chen, Y.D.[Yi-Dong],
Optimal robust classifiers,
PR(38), No. 10, October 2005, pp. 1520-1532.
Elsevier DOI 0508
BibRef

Halbe, Z.[Zohar], Aladjem, M.[Mayer],
Model-Based Mixture Discriminant Analysis: An Experimental Study,
PR(38), No. 3, March 2005, pp. 437-440.
Elsevier DOI 0412
BibRef

Weng, S.F.[Shi-Feng], Zhang, C.S.[Chang-Shui], Lin, Z.[Zhonglin],
Exploring the structure of supervised data by Discriminant Isometric Mapping,
PR(38), No. 4, April 2005, pp. 599-601.
Elsevier DOI 0501
BibRef

Demir, G.K., Ozmehmet, K.,
Online local learning algorithms for linear discriminant analysis,
PRL(26), No. 4, March 2005, pp. 421-431.
Elsevier DOI 0501
BibRef

Zheng, W.M.[Wen-Ming],
A note on kernel uncorrelated discriminant analysis,
PR(38), No. 11, November 2005, pp. 2185-2187.
Elsevier DOI 0509
BibRef

Pang, S.N.[Shao-Ning], Ozawa, S., Kasabov, N.,
Incremental linear discriminant analysis for classification of data streams,
SMC-B(35), No. 5, October 2005, pp. 905-914.
IEEE DOI 0510
BibRef

Zhao, Q.J.[Qi-Jun], Lu, H.T.[Hong-Tao], Zhang, D.[David],
A fast evolutionary pursuit algorithm based on linearly combining vectors,
PR(39), No. 2, February 2006, pp. 310-312.
Elsevier DOI 0512
Searches for optimal discriminant vectors through linearly combining standard bases. BibRef

Xu, Y.[Yong], Zhang, D.[David], Jin, Z.[Zhong], Li, M.[Miao], Yang, J.Y.[Jing-Yu],
A fast kernel-based nonlinear discriminant analysis for multi-class problems,
PR(39), No. 6, June 2006, pp. 1026-1033.
Elsevier DOI 0604
Fisher discriminant analysis; Kernel-based nonlinear discriminant analysis; Fast kernel-based nonlinear method; Face recognition BibRef

Zhu, M.L.[Man-Li], Martinez, A.M.[Aleix M.],
Subclass Discriminant Analysis,
PAMI(28), No. 8, August 2006, pp. 1274-1286.
IEEE DOI 0606
BibRef
Earlier:
Optimal Subclass Discovery for Discriminant Analysis,
LCV04(97).
IEEE DOI 0406
BibRef

Hamsici, O.C.[Onur C.], Martinez, A.M.[Aleix M.],
Bayes Optimality in Linear Discriminant Analysis,
PAMI(30), No. 4, April 2008, pp. 647-657.
WWW Link. 0803
BibRef
Earlier:
Sparse Kernels for Bayes Optimal Discriminant Analysis,
ComponentAnalysis07(1-7).
IEEE DOI 0706
BibRef

Martinez, A.M.[Aleix M.], Hamsici, O.C.[Onur C.],
Who is LB1? Discriminant analysis for the classification of specimens,
PR(41), No. 11, November 2008, pp. 3436-3441.
Elsevier DOI 0808
Pattern recognition; Paleontology; Discriminant analysis; Morphological model; Physical anthropology; Homo floresiensis BibRef

You, D.[Di], Hamsici, O.C.[Onur C.], Martinez, A.M.[Aleix M.],
Kernel Optimization in Discriminant Analysis,
PAMI(33), No. 3, March 2011, pp. 631-638.
IEEE DOI 1102
To derive non-linear classifier. Applied in several kernel discriminant analysis algorithms. BibRef

You, D.[Di], Martinez, A.M.[Aleix M.],
Bayes optimal kernel discriminant analysis,
CVPR10(3533-3538).
IEEE DOI 1006
BibRef

Wu, X.H.[Xiao-Hong], Zhou, J.J.[Jian-Jiang],
Fuzzy discriminant analysis with kernel methods,
PR(39), No. 11, November 2006, pp. 2236-2239.
Elsevier DOI 0608
Kernel methods; Kernel fuzzy discriminant analysis BibRef

Guo, Y.F.[Yue-Fei], Wu, L.D.[Li-De], Lu, H.[Hong], Feng, Z.[Zhe], Xue, X.Y.[Xiang-Yang],
Null Foley-Sammon transform,
PR(39), No. 11, November 2006, pp. 2248-2251.
Elsevier DOI 0608
Linear discriminant analysis; Feature extraction; Fisher criterion; Foley-Sammon transform
See also optimal set of discriminant vectors, An. BibRef

Dai, G.[Guang], Yeung, D.Y.[Dit-Yan], Qian, Y.T.[Yun-Tao],
Face recognition using a kernel fractional-step discriminant analysis algorithm,
PR(40), No. 1, January 2007, pp. 229-243.
Elsevier DOI 0611
Face Recognition; Feature extraction; Nonlinear dimensionality reduction; Kernel discriminant analysis; Kernel fractional-step discriminant analysis BibRef

Dai, G.[Guang], Qian, Y.T.[Yun-Tao], Jia, S.[Sen],
A kernel fractional-step nonlinear discriminant analysis for pattern recognition,
ICPR04(II: 431-434).
IEEE DOI 0409
BibRef

Dai, G.[Guang], Qian, Y.T.[Yun-Tao],
Kernel generalized nonlinear discriminant analysis algorithm for pattern recognition,
ICIP04(IV: 2697-2700).
IEEE DOI 0505
BibRef

Zhang, Y.[Yu], Yeung, D.Y.[Dit-Yan],
Semi-Supervised Discriminant Analysis using robust path-based similarity,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Liu, J.[Jun], Chen, S.C.[Song-Can], Tan, X.Y.[Xiao-Yang],
A study on three linear discriminant analysis based methods in small sample size problem,
PR(41), No. 1, January 2008, pp. 102-116.
Elsevier DOI 0710
Regularized discriminant analysis (RDA); Discriminant common vectors (DCV); Maximal margin criterion (MMC); Small sample size (SSS); Eigenvalue distribution BibRef

Yu, X., Wang, X., Liu, B.,
A Direct Kernel Uncorrelated Discriminant Analysis Algorithm,
SPLetters(14), No. 10, October 2007, pp. 742-745.
IEEE DOI 0711
BibRef

Halbe, Z.[Zohar], Aladjem, M.[Mayer],
Regularized mixture discriminant analysis,
PRL(28), No. 15, 1 November 2007, pp. 2104-2115.
Elsevier DOI 0711
Gaussian mixture models; Model selection; Bayesian information criterion; Classification; Regularized discriminant analysis BibRef

Guo, P.[Ping], Jia, Y.D.[Yun-De], Lyu, M.R.[Michael R.],
A study of regularized Gaussian classifier in high-dimension small sample set case based on MDL principle with application to spectrum recognition,
PR(41), No. 9, September 2008, pp. 2842-2854.
Elsevier DOI 0806
Classification; Covariance matrix estimation; Discriminant analysis method; Regularization parameter selection; Minimum description length BibRef

Zhang, W.Q.[Wei-Qiang], Liu, J.[Jia],
An Equalized Heteroscedastic Linear Discriminant Analysis Algorithm,
SPLetters(15), No. 1, 2008, pp. 585-588.
IEEE DOI 0811
BibRef

Pe, K.[Kalska], Haasdonk, B.[Bernard],
Kernel Discriminant Analysis for Positive Definite and Indefinite Kernels,
PAMI(31), No. 6, June 2009, pp. 1017-1032.
IEEE DOI 0904
BibRef

Haasdonk, B.[Bernard], Pekalska, E.[Elÿzbieta],
Indefinite Kernel Fisher Discriminant,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Na, J.H.[Jin Hee], Park, M.S.[Myoung Soo], Choi, J.Y.[Jin Young],
Linear boundary discriminant analysis,
PR(43), No. 3, March 2010, pp. 929-936.
Elsevier DOI 1001
Feature extraction; Linear boundary discriminant analysis; Boundary/non-boundary pattern BibRef

Suzuki, M.[Michitaka], Itoh, A.[Akiyoshi],
Reduction of processing time for optimal and quadratic discriminant analyses,
PR(43), No. 9, September 2010, pp. 3144-3150.
Elsevier DOI 1006
Optimal discriminant analysis; Quadratic discriminant analysis; Fast algorithm; Character recognition BibRef

Chai, J.[Jing], Liu, H.W.[Hong-Wei], Bao, Z.[Zheng],
Generalized re-weighting local sampling mean discriminant analysis,
PR(43), No. 10, October 2010, pp. 3422-3432.
Elsevier DOI 1007
Pattern recognition; Linear discriminant analysis; Local sampling mean discriminant analysis; Generalized re-weighting framework; Classification BibRef

Salmen, J.[Jan], Schlipsing, M.[Marc], Igel, C.[Christian],
Efficient update of the covariance matrix inverse in iterated linear discriminant analysis,
PRL(31), No. 13, 1 October 2010, pp. 1903-1907.
Elsevier DOI 1003
LDA; Feature selection; Feature optimization; Meta-heuristics; Covariance matrix update BibRef

An, S.J.[Sen-Jian], Liu, W.Q.[Wan-Quan], Venkatesh, S.[Svetha], Yan, H.[Hong],
Unified formulation of linear discriminant analysis methods and optimal parameter selection,
PR(44), No. 2, February 2011, pp. 307-319.
Elsevier DOI 1011
Linear discriminant analysis; Model selection; Under-sampled problem; Face recognition; Principal component analysis; Constrained ridge regression BibRef

Heo, G.Y.[Gyeong-Yong], Gader, P.D.[Paul D.],
Robust kernel discriminant analysis using fuzzy memberships,
PR(44), No. 3, March 2011, pp. 716-723.
Elsevier DOI 1011
Linear discriminant analysis; Kernel methods; Fuzzy memberships; Reconstruction error; Robust membership calculation BibRef

Zhang, H.H.[Hai-Hong], Guan, C.T.[Cun-Tai], Li, Y.Q.[Yuan-Qing],
A linear discriminant analysis method based on mutual information maximization,
PR(44), No. 4, April 2011, pp. 877-885.
Elsevier DOI 1101
Discriminant analysis; Mutual information; Feature extraction BibRef

Zhang, H.H.[Hai-Hong], Guan, C.T.[Cun-Tai], Ang, K.K.[Kai Keng],
An Information Theoretic Linear Discriminant Analysis Method,
ICPR10(4182-4185).
IEEE DOI 1008
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Zhang, L.H.[Lei-Hong],
Uncorrelated trace ratio linear discriminant analysis for undersampled problems,
PRL(32), No. 3, 1 February 2011, pp. 476-484.
Elsevier DOI 1101
Dimension reduction; Fisher criterion; Linear discriminant analysis; The ratio trace criterion; The trace ratio criterion; The uncorrelated LDA BibRef

Kim, T.K.[Tae-Kyun], Stenger, B.[Björn], Kittler, J.V.[Josef V.], Cipolla, R.[Roberto],
Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications,
IJCV(91), No. 2, January 2011, pp. 216-232.
WWW Link. 1101
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Kim, T.K.[Tae-Kyun], Wong, S.F.[Shu-Fai], Stenger, B.[Bjorn], Kittler, J.V.[Josef V.], Cipolla, R.[Roberto],
Incremental Linear Discriminant Analysis Using Sufficient Spanning Set Approximations,
CVPR07(1-8).
IEEE DOI 0706
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Yang, J.[Jian], Zhang, L.[Lei], Yang, J.Y.[Jing-Yu], Zhang, D.[David],
From classifiers to discriminators: A nearest neighbor rule induced discriminant analysis,
PR(44), No. 7, July 2011, pp. 1387-1402.
Elsevier DOI 1103
Classification; Classifier; Feature extraction; Discriminant analysis; Dimensionality reduction; Pattern recognition BibRef

Yang, J.[Jian], Zhang, L.[Lei], Xu, Y.[Yong], Yang, J.Y.[Jing-Yu],
Beyond sparsity: The role of L1-optimizer in pattern classification,
PR(45), No. 3, March 2012, pp. 1104-1118.
Elsevier DOI 1111
Sparse representation; Pattern classification; Classifier; Feature extraction BibRef

Zhang, J.[Jian], Yang, J.[Jian],
Linear reconstruction measure steered nearest neighbor classification framework,
PR(47), No. 4, 2014, pp. 1709-1720.
Elsevier DOI 1402
Linear reconstruction measure (LRM) BibRef

An, S.[Shounan], Yoo, J.[Jiho], Choi, S.J.[Seung-Jin],
Manifold-respecting discriminant nonnegative matrix factorization,
PRL(32), No. 6, 15 April 2011, pp. 832-837.
Elsevier DOI 1103
Discriminant analysis; Manifold regularization; Nonnegative matrix factorization BibRef

Nie, F.P.[Fei-Ping], Xiang, S.M.[Shi-Ming], Liu, Y.[Yun], Hou, C.P.[Chen-Ping], Zhang, C.S.[Chang-Shui],
Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction,
PRL(33), No. 5, 1 April 2012, pp. 485-491.
Elsevier DOI 1202
Least squares; Subspace learning; Discriminant analysis; Feature extraction; Image recognition BibRef

Françoisse, K.[Kevin], Fouss, F.[François], Saerens, M.[Marco],
A link-analysis-based discriminant analysis for exploring partially labeled graphs,
PRL(34), No. 2, 15 January 2013, pp. 146-154.
Elsevier DOI 1212
Discriminant analysis; Link analysis; Semi-supervised classification; Graph mining; Dimensionality reduction; Kernels on a graph BibRef

Yeh, Y.R.[Yi-Ren], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
A rank-one update method for least squares linear discriminant analysis with concept drift,
PR(46), No. 5, May 2013, pp. 1267-1276.
Elsevier DOI 1302
Linear discriminant analysis; Least squares solution; Rank-one update; Concept drift BibRef

Yeh, Y.R.[Yi-Ren], Huang, C.H.[Chun-Hao], Wang, Y.C.F.,
Heterogeneous Domain Adaptation and Classification by Exploiting the Correlation Subspace,
IP(23), No. 5, May 2014, pp. 2009-2018.
IEEE DOI 1405
image classification BibRef

Chen, X.B.[Xiao-Bo], Yang, J.[Jian], Zhang, D.[David], Liang, J.[Jun],
Complete large margin linear discriminant analysis using mathematical programming approach,
PR(46), No. 6, June 2013, pp. 1579-1594.
Elsevier DOI 1302
Feature extraction; Linear discriminant analysis; Large margin classifier; Constrained concave-convex procedure BibRef

Zhi, X.B.[Xiao-Bin], Fan, J.L.[Jiu-Lun], Zhao, F.[Feng],
Fuzzy Linear Discriminant Analysis-guided maximum entropy fuzzy clustering algorithm,
PR(46), No. 6, June 2013, pp. 1604-1615.
Elsevier DOI 1302
Fuzzy scatter matrix; Fuzzy Linear Discriminant Analysis; Optimal transformation matrix; Maximum entropy fuzzy clustering algorithm BibRef

Xing, X.L.[Xiang-Lei], Du, S.[Sidan], Jiang, H.[Hua],
Semi-Supervised Nonparametric Discriminant Analysis,
IEICE(E96-D), No. 2, February 2013, pp. 375-378.
WWW Link. 1301
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Leung, K.C., Leung, C.H.,
Dynamic discriminant functions with missing feature values,
PRL(34), No. 13, 2013, pp. 1548-1556.
Elsevier DOI 1308
Fisher's linear discriminant BibRef

Lai, Z., Xu, Y., Yang, J., Tang, J., Zhang, D.,
Sparse tensor discriminant analysis,
IP(22), No. 10, 2013, pp. 3904-3915.
IEEE DOI 1309
Linear discriminant analysis BibRef

de Lima, M.S.[Max Sousa], Pereira, J.R.G.[Jose R.G.], Souza, D.S.[Diego Silva],
Bayesian predictive kernel discriminant analysis,
PRL(34), No. 16, 2013, pp. 2079-2085.
Elsevier DOI 1310
Discriminant analysis BibRef

Zhao, H.T.[Hai-Tao], Wong, W.K.,
Regularized discriminant entropy analysis,
PR(47), No. 2, 2014, pp. 806-819.
Elsevier DOI 1311
Regularized discriminant entropy BibRef

Guo, J.[Jia], Huang, H.[Hu], Chen, C.[Cheng], Rohde, G.K.,
Optimized Nonlinear Discriminant Analysis (ONDA) for Supervised Pixel Classification,
SPLetters(20), No. 12, 2013, pp. 1155-1158.
IEEE DOI 1311
channel bank filters BibRef

Tahir, M.A., Yan, F.[Fei], Koniusz, P., Awais, M., Barnard, M., Mikolajczyk, K., Bouridane, A., Kittler, J.V.,
A Robust and Scalable Visual Category and Action Recognition System Using Kernel Discriminant Analysis With Spectral Regression,
MultMed(15), No. 7, 2013, pp. 1653-1664.
IEEE DOI 1312
computational complexity BibRef

Tahir, M.A., Kittler, J.V., Mikolajczyk, K., Yan, F., van de Sande, K.E.A., Gevers, T.,
Visual category recognition using Spectral Regression and Kernel Discriminant Analysis,
Subspace09(178-185).
IEEE DOI 0910
BibRef

Tao, Y.T.[Yu-Ting], Yang, J.[Jian], Chang, H.[Heyou],
Enhanced iterative projection for subclass discriminant analysis under EM-alike framework,
PR(47), No. 3, 2014, pp. 1113-1125.
Elsevier DOI 1312
Linear discriminant analysis BibRef

Hayashi, K.[Kuniyoshi],
Influence functions for a linear subspace method,
PR(47), No. 6, 2014, pp. 2241-2254.
Elsevier DOI 1403
CLAFIC BibRef

Ly, N.H.[Nam Hoai], Du, Q.[Qian], Fowler, J.E.[James E.],
Sparse Graph-Based Discriminant Analysis for Hyperspectral Imagery,
GeoRS(52), No. 7, July 2014, pp. 3872-3884.
IEEE DOI 1403
Eigenvalues and eigenfunctions BibRef

Li, W.[Wei], Prasad, S.[Saurabh], Fowler, J.E.[James E.], Bruce, L.M.[Lori Mann],
Locality-Preserving Dimensionality Reduction and Classification for Hyperspectral Image Analysis,
GeoRS(50), No. 4, April 2012, pp. 1185-1198.
IEEE DOI 1204
BibRef

Feng, F.B.[Fu-Biao], Li, W.[Wei], Du, Q.[Qian], Zhang, B.[Bing],
Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
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Deng, Y., Li, H., Fu, K., Du, Q., Emery, W.J.,
Tensor Low-Rank Discriminant Embedding for Hyperspectral Image Dimensionality Reduction,
GeoRS(56), No. 12, December 2018, pp. 7183-7194.
IEEE DOI 1812
Tensile stress, Feature extraction, Hyperspectral imaging, Robustness, Dimensionality reduction, Data models, Classification, tensor BibRef

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GeoRS(58), No. 3, March 2020, pp. 1630-1643.
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Feature extraction, Germanium, Hyperspectral imaging, Manifolds, Dimensionality reduction, Classification, tensor analysis BibRef

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feature extraction, hyperspectral imaging, image classification, learning (artificial intelligence), neural nets, pattern recognition BibRef

Li, Y.[Yuan], Xu, Q.Z.[Qi-Zhi], Li, W.[Wei], Nie, J.Y.[Jin-Yan],
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Strips, Spectral shape, Convolution, Roads, Neural networks, Interference, Feature extraction, Automatic clustering, hyperspectral image (HSI) BibRef

Pan, L.[Lei], Li, H.C.[Heng-Chao], Deng, Y.J.[Yang-Jun], Zhang, F.[Fan], Chen, X.D.[Xiang-Dong], Du, Q.[Qian],
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Hyperspectral imaging, Kernel, Laplace equations, Manifolds, Principal component analysis, Sparse matrices, Dimensionality reduction (DR), graph embedding (GE), hyperspectral image, kernel methods, sparse, and, low-rank, graph BibRef

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Wang, H.X.[Hai-Xian], Zheng, W.M.[Wen-Ming], Hu, Z.[Zilan], Chen, S.B.[Si-Bao],
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ICIP19(3841-3845)
IEEE DOI 1910
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belief networks, image classification, inference mechanisms, learning (artificial intelligence), CVB-LGDA, topic modeling BibRef

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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Training Set Size, Sample Size, Analysis, Selection .