14.2.16 Fisher, Parzen, and Other Clustering Measures and Decompositions

Fisher, R.A.,
On a distribution yielding the error functions of several well-known statistics,
Proc Int Congr Math(2), 1924, pp. 805-813. BibRef 2400

Fisher, R.A.,
The Use of Multiple Measurements in Taxonomic Problems,
Annals of Eugenics(7), 1936, pp. 179-188. Fisher Discriminant. BibRef 3600

Fisher, R.A.,
The Statistical Utilization of Multiple Measurements,
Annals of Eugenics(8), 1938, pp. 376-386. BibRef 3800

Parzen, E.,
On Estimation of a Probability Density Function and Mode,
AMS(33), September 1962, pp. 1065-1076. BibRef 6209

Shanmugam, K.S.,
On a modified form of Parzen estimator for nonparametric pattern recognition,
PR(9), No. 3, October 1977, pp. 167-170.
Elsevier DOI 0309
BibRef

Longstaff, I.D.,
On Extensions to Fisher's Linear Discriminant Function,
PAMI(9), No. 2, March 1987, pp. 321-325. BibRef 8703

Duchene, J., and Leclercq, S.,
An Optimal Transformation for Discriminant and Principal Component Analysis,
PAMI(10), No. 6, November 1988, pp. 978-983.
IEEE DOI BibRef 8811

Fukunaga, K., and Hayes, R.R.,
The Reduced Parzen Classifier,
PAMI(11), No. 4, April 1989, pp. 423-425.
IEEE DOI BibRef 8904

Liu, S.D.D.[Shiaw-Dong D.], Casasent, D.P.[David P.],
Iterative Fisher/Minimum-Variance Optical Classifier,
PR(23), No. 3-4, 1990, pp. 385-391.
Elsevier DOI 0401
BibRef

Cheng, Y.Q.[Yong-Qing], Zhuang, Y.M.[Yong-Ming], Yang, J.Y.[Jing-Yu],
Optimal Fisher discriminant analysis using the rank decomposition,
PR(25), No. 1, January 1992, pp. 101-111.
Elsevier DOI 0401
BibRef

Yang, J.[Jian], Yang, J.Y.[Jing-Yu], and Zhang, D.[David],
What's wrong with Fisher criterion?,
PR(35), No. 11, November 2002, pp. 2665-2668.
Elsevier DOI 0208
BibRef

Xu, Y.[Yong], Yang, J.Y.[Jing-Yu], Jin, Z.[Zhong],
A novel method for Fisher discriminant analysis,
PR(37), No. 2, February 2004, pp. 381-384.
Elsevier DOI 0311
BibRef

Xu, Y.[Yong], Yang, J.Y.[Jing-Yu], Yang, J.[Jian],
A reformative kernel Fisher discriminant analysis,
PR(37), No. 6, June 2004, pp. 1299-1302.
Elsevier DOI 0405
BibRef

Jeon, B.W.[Byeung-Woo], Landgrebe, D.A.,
Fast Parzen Density-Estimation Using Clustering-Based Branch-And-Bound,
PAMI(16), No. 9, September 1994, pp. 950-954.
IEEE DOI
PDF File. BibRef 9409

Babich, G.A., Camps, O.I.,
Weighted Parzen Windows For Pattern-Classification,
PAMI(18), No. 5, May 1996, pp. 567-570.
IEEE DOI 9606
BibRef

Hamamoto, Y.[Yoshihiko], Fujimoto, Y.S.[Yasu-Shi], Tomita, S.[Shingo],
On the Estimation of a Covariance-matrix in Designing Parzen Classifiers,
PR(29), No. 10, October 1996, pp. 1751-1759.
Elsevier DOI Kernel Covariance. BibRef 9610

Kraaijveld, M.A.,
A Parzen Classifier with an Improved Robustness Against Deviations Between Training and Test Data,
PRL(17), No. 7, June 10 1996, pp. 679-689. 9607
BibRef

Hand, D.J., Oliver, J.J., Lunn, A.D.,
Discriminant-Analysis When The Classes Arise From A Continuum,
PR(31), No. 5, May 1998, pp. 641-650.
Elsevier DOI 9805
BibRef

Gan, W.S.,
Designing a Fuzzy Step Size LMS Algorithm,
VISP(144), No. 5, October 1997, pp. 261-266. 9806
BibRef

Raudys, S.J., Duin, R.P.W.,
Expected Classification Error of the Fisher Linear Classifier with Pseudo Inverse Covariance Matrix,
PRL(19), No. 5-6, April 1998, pp. 385-392. 9808
BibRef

Raudys, S.J., Diciunas, V.,
Expected Error of Minimum Empirical Error and Maximal Margin Classifiers,
ICPR96(II: 875-879).
IEEE DOI 9608
(Institute of Mathematics and Informatics, LIT) BibRef

Postona, W.L.[Wendy L.], Marchettea, D.J.[David J.],
Recursive Dimensionality Reduction Using Fishers Linear Discriminant,
PR(31), No. 7, July 1998, pp. 881-888.
Elsevier DOI 9807
BibRef

Roberts, S.J.[Stephen J.], Everson, R.[Richard], Rezek, I.[Iead],
Maximum certainty data partitioning,
PR(33), No. 5, May 2000, pp. 833-839.
Elsevier DOI 0003
BibRef

Zhu, Q.M.[Qiu-Ming], Cai, Y.[Yao], Liu, L.Z.[Lu-Zheng],
A multiple hyper-ellipsoidal subclass model for an evolutionary classifier,
PR(34), No. 3, March 2001, pp. 547-560.
Elsevier DOI 0101
BibRef

Cooke, T.[Tristrom],
Two Variations on Fisher's Linear Discriminant for Pattern Recognition,
PAMI(24), No. 2, February 2002, pp. 268-273.
IEEE DOI 0202
BibRef

Sierra, A.,
High-order Fisher's discriminant analysis,
PR(35), No. 6, June 2002, pp. 1291-1302.
Elsevier DOI 0203
BibRef

Girolami, M.A., He, C.[Chao],
Probability density estimation from optimally condensed data samples,
PAMI(25), No. 10, October 2003, pp. 1253-1264.
IEEE Abstract. 0310
Parzen window estimator. BibRef

Mika, S.[Sebastian], Ratsch, G.[Gunnar], Weston, J.[Jason], Scholkopf, B.[Bernhard], Smola, A.J.[Alexander J.], Muller, K.R.[Klaus-Robert],
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces,
PAMI(25), No. 5, May 2003, pp. 623-628.
IEEE Abstract. 0304
Nonlinear generalization of Fisher's discriminant and oriented PCA. BibRef

Cawley, G.C.[Gavin C.], Talbot, N.L.C.[Nicola L. C.],
Efficient Leave-One-Out Cross-Validation of Kernel Fisher Discriminant Classifiers,
PR(36), No. 11, November 2003, pp. 2585-2592.
Elsevier DOI 0309
BibRef

Song, F.X.[Feng-Xi], Liu, S.H.[Shu-Hai], Yang, J.Y.[Jing-Yu],
Orthogonalized Fisher discriminant,
PR(38), No. 2, February 2005, pp. 311-313.
Elsevier DOI 0411
BibRef

Zhuang, X.S.[Xiao-Sheng], Dai, D.Q.[Dao-Qing],
Inverse Fisher discriminate criteria for small sample size problem and its application to face recognition,
PR(38), No. 11, November 2005, pp. 2192-2194.
Elsevier DOI 0509
BibRef

Xu, M., Wu, X., Franti, P.,
Context Quantization by Kernel Fisher Discriminant,
IP(15), No. 1, January 2006, pp. 169-177.
IEEE DOI 0601
BibRef

Tao, Q.[Qing], Wu, G.W.[Gao-Wei], Wang, J.[Jue],
The theoretical analysis of FDA and applications,
PR(39), No. 6, June 2006, pp. 1199-1204.
Elsevier DOI Fisher discriminant analysis; Support vector machines; LS-SVM (least squares SVM); Regression 0604
BibRef

Xie, J.G.[Ji-Gang], Qiu, Z.D.[Zheng-Ding], Miao, Z.J.[Zhen-Jiang], Zhang, Y.Q.[Yan-Qiang],
Bootstrap FDA for counting positives accurately in imprecise environments,
PR(40), No. 11, November 2007, pp. 3292-3298.
Elsevier DOI 0707
Bootstrap; Small sample; Binary classification; Fisher discriminant analysis BibRef

Zhang, S.[Sheng], Sim, T.[Terence],
Discriminant Subspace Analysis: A Fukunaga-Koontz Approach,
PAMI(29), No. 10, October 2007, pp. 1732-1745.
IEEE DOI 0710
Survey, Discrminiant Analysis. BibRef
Earlier:
When Fisher meets Fukunaga-Koontz: A New Look at Linear Discriminants,
CVPR06(I: 323-329).
IEEE DOI 0606

See also Application of the Karhunen-Loeve Expansion to Feature Selection and Ordering. Analyze the techniques and show the relationships. BibRef

Sim, T.[Terence], Zhang, S.[Sheng], Li, J.[Jianran], Chen, Y.[Yan],
Simultaneous and orthogonal decomposition of data using Multimodal Discriminant Analysis,
ICCV09(452-459).
IEEE DOI 0909
BibRef

Zhang, S.[Sheng], Sim, T.[Terence], Yeh, M.C.[Mei-Chen],
Identity and Variation Spaces: Revisiting the Fisher Linear Discriminant,
Subspace09(123-130).
IEEE DOI 0910
BibRef

Chen, B.[Bo], Liu, H.W.[Hong-Wei], Bao, Z.[Zheng],
A kernel optimization method based on the localized kernel Fisher criterion,
PR(41), No. 3, March 2008, pp. 1098-1109.
Elsevier DOI 0711
Kernel machine; Fisher criterion; Kernel optimization; Kernel induced feature space; Radar automatic target recognition (RATR); High-resolution range profile (HRRP) BibRef

Chen, B.[Bo], Liu, H.W.[Hong-Wei], Bao, Z.[Zheng],
Optimizing the data-dependent kernel under a unified kernel optimization framework,
PR(41), No. 6, June 2008, pp. 2107-2119.
Elsevier DOI 0802
Kernel machine; Fisher criteria; Kernel optimization; Kernel induced feature space BibRef

Zhang, D.Q.[Dao-Qiang], Chen, S.C.[Song-Can], Zhou, Z.H.[Zhi-Hua],
Constraint Score: A new filter method for feature selection with pairwise constraints,
PR(41), No. 5, May 2008, pp. 1440-1451.
Elsevier DOI 0711
Feature selection; Pairwise constraints; Filter method; Constraint Score; Fisher Score; Laplacian Score BibRef

Harrison, R.F.[Robert F.], Pasupa, K.[Kitsuchart],
Sparse multinomial kernel discriminant analysis (sMKDA),
PR(42), No. 9, September 2009, pp. 1795-1802.
Elsevier DOI 0905
Linear discriminant analysis; Kernel discriminant analysis; Multi-class; Multinomial; Least-squares; Optimal scaling; Sparsity control BibRef

Pasupa, K.[Kitsuchart], Harrison, R.F.[Robert F.], Willett, P.[Peter],
Parsimonious Kernel Fisher Discrimination,
IbPRIA07(I: 531-538).
Springer DOI 0706
BibRef

Carter, K.M.[Kevin M.], Raich, R.[Raviv], Finn, W.G.[William G.], Hero, III, A.O.[Alfred O.],
FINE: Fisher Information Nonparametric Embedding,
PAMI(31), No. 11, November 2009, pp. 2093-2098.
IEEE DOI 0910
BibRef

Hoyle, D.C.[David C.],
Accuracy of Pseudo-Inverse Covariance Learning: A Random Matrix Theory Analysis,
PAMI(33), No. 7, July 2011, pp. 1470-1481.
IEEE DOI 1106
When sample point set is too small. BibRef

Gao, Q.X.[Quan-Xue], Liu, J.J.[Jing-Jing], Zhang, H.J.[Hai-Jun], Hou, J.[Jun], Yang, X.J.[Xiao-Jing],
Enhanced fisher discriminant criterion for image recognition,
PR(45), No. 10, October 2012, pp. 3717-3724.
Elsevier DOI 1206
Fisher linear discriminant analysis; Within-class variation; Dimensionality reduction BibRef

Rozza, A.[Alessandro], Lombardi, G.[Gabriele], Casiraghi, E.[Elena], Campadelli, P.[Paola],
Novel Fisher discriminant classifiers,
PR(45), No. 10, October 2012, pp. 3725-3737.
Elsevier DOI 1206
Fisher subspace; Supervised learning; Discriminant techniques; Small sample size problem BibRef

Diaf, A., Boufama, B., Benlamri, R.,
Non-parametric Fisher's discriminant analysis with kernels for data classification,
PRL(34), No. 5, 1 April 2013, pp. 552-558.
Elsevier DOI 1303
Data classification; Kernel trick; NDA algorithm; Discriminant analysis; Eigenspace BibRef

Besson, O., Abramovich, Y.I.,
On the Fisher Information Matrix for Multivariate Elliptically Contoured Distributions,
SPLetters(20), No. 11, 2013, pp. 1130-1133.
IEEE DOI 1310
Abstracts BibRef

Abramovich, Y.I., Besson, O.,
On the Expected Likelihood Approach for Assessment of Regularization Covariance Matrix,
SPLetters(22), No. 6, June 2015, pp. 777-781.
IEEE DOI 1411
Bayes methods BibRef

Daqi, G.[Gao], Jun, D.[Ding], Changming, Z.[Zhu],
Integrated Fisher linear discriminants: An empirical study,
PR(47), No. 2, 2014, pp. 789-805.
Elsevier DOI 1311
Fisher linear discriminants BibRef

Stein, M., Mezghani, A., Nossek, J.A.,
A Lower Bound for the Fisher Information Measure,
SPLetters(21), No. 7, July 2014, pp. 796-799.
IEEE DOI 1405
Additive noise BibRef

Bian, W., Tao, D.,
Asymptotic Generalization Bound of Fisher's Linear Discriminant Analysis,
PAMI(36), No. 12, December 2014, pp. 2325-2337.
IEEE DOI 1411
Asymptotic stability BibRef

Wu, X.Y.[Xing-Yu], Mao, X.[Xia], Chen, L.J.[Li-Jiang], Xue, Y.[Yuli], Rovetta, A.[Alberto],
Kernel optimization using nonparametric Fisher criterion in the subspace,
PRL(54), No. 1, 2015, pp. 43-49.
Elsevier DOI 1502
Dimensionality reduction BibRef

Sánchez, J.[Jorge], Redolfi, J.[Javier],
Exponential family Fisher vector for image classification,
PRL(59), No. 1, 2015, pp. 26-32.
Elsevier DOI 1505
Image classification BibRef

Mussa, H.Y.[Hamse Y.], Mitchell, J.B.O.[John B.O.], Afzal, A.M.[Avid M.],
The Parzen Window method: In terms of two vectors and one matrix,
PRL(63), No. 1, 2015, pp. 30-35.
Elsevier DOI 1508
Probability density function BibRef

Fan, Z.Z.[Zi-Zhu], Xu, Y.[Yong], Ni, M.[Ming], Fang, X.Z.[Xiao-Zhao], Zhang, D.[David],
Individualized learning for improving kernel Fisher discriminant analysis,
PR(58), No. 1, 2016, pp. 100-109.
Elsevier DOI 1606
Individualized learning BibRef

Ye, H.S.[Hai-Shan], Li, Y.J.[Yu-Jun], Chen, C.[Cheng], Zhang, Z.H.[Zhi-Hua],
Fast Fisher discriminant analysis with randomized algorithms,
PR(72), No. 1, 2017, pp. 82-92.
Elsevier DOI 1708
Fisher discriminant analysis BibRef

Zhu, J., Han, L., Blum, R.S., Xu, Z.,
On the Analysis of the Fisher Information of a Perturbed Linear Model After Random Compression,
SPLetters(25), No. 1, January 2018, pp. 100-104.
IEEE DOI 1801
data compression, matrix algebra, perturbation techniques, random processes, Crame´r-Rao bound, FIM, random compression BibRef

Ahmed, S.[Sarah], Azim, T.[Tayyaba],
Diversified Fisher kernel: encoding discrimination in Fisher features to compete deep neural models for visual classification task,
IET-CV(14), No. 8, December 2020, pp. 658-664.
DOI Link 2012
BibRef

Chang, C.C.[Chin-Chun],
Fisher's Linear Discriminant Analysis With Space-Folding Operations,
PAMI(45), No. 7, July 2023, pp. 9233-9240.
IEEE DOI 2306
Training, Feature extraction, Covariance matrices, Linear discriminant analysis, Feedforward neural networks, rectified linear units BibRef

Liu, J.[Jiamin], Xu, W.[Wangli], Zhang, F.[Fode], Lian, H.[Heng],
Properties of Standard and Sketched Kernel Fisher Discriminant,
PAMI(45), No. 8, August 2023, pp. 10596-10602.
IEEE DOI 2307
Kernel, Convergence, Sociology, Eigenvalues and eigenfunctions, Estimation, Standards, Urban areas, Kernel method, random projection, variance operator BibRef

Ghojogh, B.[Benyamin], Sikaroudi, M.[Milad], Tizhoosh, H.R., Karray, F.[Fakhri], Crowley, M.[Mark],
Weighted Fisher Discriminant Analysis in the Input and Feature Spaces,
ICIAR20(II:3-15).
Springer DOI 2007
BibRef

Jiang, Y., Leung, F.H.F.,
Generalized Fisher Discriminant Analysis as A Dimensionality Reduction Technique,
ICPR18(994-999)
IEEE DOI 1812
Kernel, Linear programming, Speaker recognition, Principal component analysis, Dimensionality reduction, speaker recognition BibRef

Diba, A., Pazandeh, A.M., Van Gool, L.J.,
Deep visual words: Improved fisher vector for image classification,
MVA17(186-189)
DOI Link 1708
Encoding, Feature extraction, Image coding, Neural networks, Pipelines, Training, Visualization BibRef

Ilea, I.[Ioana], Bombrun, L.[Lionel], Germain, C.[Christian], Terebes, R.[Romulus], Borda, M.[Monica],
Statistical hypothesis test for robust classification on the space of covariance matrices,
ICIP15(271-275)
IEEE DOI 1512
Robust image classification BibRef

Zuluaga, C.D.[Carlos D.], Valencia, E.A.[Edgar A.], Álvarez, M.A.[Mauricio A.], Orozco, Á.A.[Álvaro A.],
A Parzen-Based Distance Between Probability Measures as an Alternative of Summary Statistics in Approximate Bayesian Computation,
CIAP15(I:50-61).
Springer DOI 1511
BibRef

Peng, J.[Jing], Seetharaman, G.,
On Parzen windows classifiers,
AIPR14(1-4)
IEEE DOI 1504
estimation theory BibRef

Fujiki, J.[Jun], Tanaka, M.[Masaru], Sakano, H.[Hitoshi], Kimura, A.[Akisato],
Geometric interpretation of Fisher's linear discriminant analysis through communication theory,
MVA15(333-336)
IEEE DOI 1507
Channel capacity BibRef

Shafiee, S.[Soheil], Kamangar, F.[Farhad], Athitsos, V.[Vassilis],
A Multi-Modal Sparse Coding Classifier Using Dictionaries with Different Number of Atoms,
WACV15(518-525)
IEEE DOI 1503
Dictionaries BibRef

Shafiee, S.[Soheil], Kamangar, F.[Farhad], Athitsos, V.[Vassilis], Huang, J.Z.[Jun-Zhou], Ghandehari, L.[Laleh],
Multimodal sparse representation classification with Fisher discriminative sample reduction,
ICIP14(5192-5196)
IEEE DOI 1502
Accuracy BibRef

Rozza, A.[Alessandro], Serra, G.[Giuseppe], Grana, C.[Costantino],
Truncated isotropic principal component classifier for image classification,
ICIP14(986-990)
IEEE DOI 1502
Covariance matrices BibRef

Wang, B.X.[Bao-Xing], Yin, Q.Y.[Qi-Yue], Wu, S.[Shu], Wang, L.[Liang], Liu, G.Q.[Gui-Quan],
Discriminative Representative Selection via Structure Sparsity,
ICPR14(1401-1406)
IEEE DOI 1412
Databases. Find a few representatives in a dataset for representation and discrimination. BibRef

Yang, Y.H.[Yao-Hsiang], Chen, L.H.[Lu-Hung], Chen, C.S.[Chu-Song], Wang, C.C.[Chieh-Chih],
Fisher's Discriminant with Natural Image Priors,
ICPR14(4305-4309)
IEEE DOI 1412
Bayes methods BibRef

Baecchi, C.[Claudio], Turchini, F.[Francesco], Seidenari, L.[Lorenzo], Bagdanov, A.D.[Andrew D.], del Bimbo, A.[Alberto],
Fisher Vectors over Random Density Forests for Object Recognition,
ICPR14(4328-4333)
IEEE DOI 1412
Encoding BibRef

Wang, Q.[Quan], Shen, X.[Xin], Wang, M.[Meng], Boyer, K.L.[Kim L.],
Label Consistent Fisher Vectors for Supervised Feature Aggregation,
ICPR14(3588-3593)
IEEE DOI 1412
Accuracy BibRef

Sydorov, V.[Vladyslav], Sakurada, M.[Mayu], Lampert, C.H.[Christoph H.],
Deep Fisher Kernels: End to End Learning of the Fisher Kernel GMM Parameters,
CVPR14(1402-1409)
IEEE DOI 1409
Fisher kernel BibRef

Wang, Z.[Zhan], Ruan, Q.Q.[Qiu-Qi], Miao, Z.J.[Zhen-Jiang],
Projection-optimal tensor local Fisher discriminant analysis for image feature extraction,
ICIP13(2852-2856)
IEEE DOI 1402
Discriminant analysis BibRef

Liu, B.Y.[Ben-Yong],
Kernel discrimination via oblique projection,
IASP11(707-711).
IEEE DOI 1112
BibRef

Huttunen, H.[Heikki], Ryynänen, J.P.[Jari-Pekka], Forsvik, H.[Heikki], Voipio, V.[Ville], Kikuchi, H.[Hisakazu],
Kernel Fisher Discriminant and Elliptic Shape Model for Automatic Measurement of Allergic Reactions,
SCIA11(764-773).
Springer DOI 1105
BibRef

Yan, F.[Fei], Mikolajczyk, K.[Krystian], Barnard, M.[Mark], Cai, H.P.[Hong-Ping], Kittler, J.V.[Josef V.],
LP norm multiple kernel Fisher discriminant analysis for object and image categorisation,
CVPR10(3626-3632).
IEEE DOI 1006
BibRef

Fang, Y.[Youhan], Shan, S.G.[Shi-Guang], Chang, H.[Hong], Chen, X.L.[Xi-Lin], Gao, W.[Wen],
Parzen Discriminant Analysis,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Mutelo, R.M., Woo, W.L., Dlay, S.S.,
A Complete Fisher Discriminant Analysis for Based Image Matrix and Its Application to Face Biometrics,
ICB07(1067-1076).
Springer DOI 0708
BibRef

Lu, F.F.[Fang-Fang], Li, H.D.[Hong-Dong],
KLDA: An Iterative Approach to Fisher Discriminant Analysis,
ICIP07(II: 201-204).
IEEE DOI 0709
BibRef

Dai, G.[Guang], Yeung, D.Y.[Dit-Yan], Chang, H.[Hong],
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion,
ECCV06(IV: 308-320).
Springer DOI 0608
BibRef

Mio, W.[Washington], Badlyans, D.[Dennis], Liu, X.W.[Xiu-Wen],
A Computational Approach to Fisher Information Geometry with Applications to Image Analysis,
EMMCVPR05(18-33).
Springer DOI 0601
BibRef

Liu, X.W.[Xiu-Wen], Mio, W.[Washington],
Splitting Factor Analysis and Multi-Class Boosting,
ICIP06(949-952).
IEEE DOI 0610
BibRef

Liu, X.W.[Xiu-Wen], Mio, W.[Washington],
Kernel Methods for Nonlinear Discriminative Data Analysis,
EMMCVPR05(584-599).
Springer DOI 0601
BibRef

Saadi, K., Talbot, N.L.C., Cawley, G.C.,
Optimally Regularised Kernel Fisher Discriminant Analysis,
ICPR04(II: 427-430).
IEEE DOI 0409
BibRef

de Ridder, D., Loog, M., Reinders, M.J.T.,
Local Fisher Embedding,
ICPR04(II: 295-298).
IEEE DOI 0409
BibRef

Vaswani, N.,
A linear classifier for gaussian class conditional distributions with unequal covariance matrices,
ICPR02(II: 60-63).
IEEE DOI 0211
BibRef

Muto, Y., Nagase, H., Hamamoto, Y.,
Evaluation of a Modified Parzen Classifier in High Dimensional Spaces,
ICPR00(Vol II: 67-70).
IEEE DOI 0009
BibRef

Sakai, M.[Mitsuru], Yoneda, M.[Masaaki], Hase, H.[Hiroyuki],
A New Robust Quadratic Discriminant Function,
ICPR98(Vol I: 99-102).
IEEE DOI 9808
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Bayesian Clustering, Bayes Classifier .