14.2.11.1 Bayesian Clustering, Bayes Classifier

Beisner, H.M.,
A recursive Bayesian approach to pattern recognition,
PR(1), No. 1, July 1968, pp. 13-31.
WWW Version. 0309 BibRef

Basu, J.P., Odell, P.L.,
Effect of intraclass correlation among training samples on the misclassification probabilities of bayes procedure,
PR(6), No. 1, June 1974, pp. 13-16.
WWW Version. 0309 BibRef

Tsokos, C.P.[Chris P.], Welch, R.L.W.,
Bayes discrimination with mean square error loss,
PR(10), No. 2, 1978, pp. 113-123.
WWW Version. 0309 BibRef

Tubbs, J.D.,
Effect of autocorrelated training samples on Bayes' probabilities of misclassification,
PR(12), No. 6, 1980, pp. 351-354.
WWW Version. 0309 BibRef

van Ness, J.W.,
On the Dominance of Non-Parametric Bayes Rule Discriminant Algorithms in High Dimensions,
PR(12), No. 6, 1980, pp. 355-368.
WWW Version. BibRef 8000

Decell, Jr., H.P.[Henry P.], Odell, P.L., Coberly, W.A.[William A.],
Linear dimension reduction and Bayes classification,
PR(13), No. 3, 1981, pp. 241-243.
WWW Version. 0309 BibRef

Tubbs, J.D., Coberly, W.A., Young, D.M.,
Linear dimension reduction and Bayes classification with unknown population parameters,
PR(15), No. 3, 1982, pp. 167-172.
WWW Version. 0309 BibRef

Postaire, J.G.,
An unsupervised Bayes classifier for normal patterns based on marginal densities analysis,
PR(15), No. 2, 1982, pp. 103-111.
WWW Version. 0309 BibRef

Jajuga, K.[Krzysztof],
Bayes classification rule for the general discrete case,
PR(19), No. 5, 1986, pp. 413-415.
WWW Version. 0309 BibRef

Toussaint, G.T.[Godfried T.],
Bayes classification rule for the general discrete case,
PR(20), No. 4, 1987, pp. 411.
WWW Version. 0309 BibRef

Kurzynski, M.W.[Marek W.],
On the multistage Bayes classifier,
PR(21), No. 4, 1988, pp. 355-365.
WWW Version. 0309 See also On the Identity of Optimal Strategies for Multistage Classifiers. See also optimal strategy of a tree classifier, The. BibRef

Garber, F.D., and Djouadi, A.,
Bounds on the Bayes Classification Error Based on Pairwise Risk Functions,
PAMI(10), No. 2, March 1988, pp. 281-288.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 8803

Hwang, S.Y.[Shu-Yuen],
Two heuristics for arranging the order of feature-extraction operations in recursive Bayesian decision rule,
PR(23), No. 12, 1990, pp. 1389-1392.
WWW Version. 0401 BibRef

Carhart, G.W., Draayer, B.F., Giles, M.K.,
Optical-Pattern Recognition Using Bayesian Classification,
PR(27), No. 4, April 1994, pp. 587-606.
WWW Version. BibRef 9404

Ruiz, A.[Alberto],
A Nonparametric Bound for the Bayes Error,
PR(28), No. 6, June 1995, pp. 921-930.
WWW Version. 0401 BibRef

Avi-Itzhak, H., Diep, T.,
Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error,
PAMI(18), No. 1, January 1996, pp. 89-91.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9601

Xu, L.,
Bayesian Ying-Yang Machine, Clustering and Number of Clusters,
PRL(18), No. 11-13, November 1997, pp. 1167-1178. 9806 BibRef

Hurn, M.A., Mardia, K.V., Hainsworth, T.J., Kirkbride, J., Berry, E.,
Bayesian fused classification of medical images,
MedImg(15), No. 6, December 1996, pp. 850-858.
IEEE Top Reference. 0203 BibRef

Mardia, K.V., Hainsworth, T.J., Kirkbride, J.,
Hierarchical Bayesian Classification of Multimodal Medical Images,
MMBIA96(Bayesian Analysis) BibRef 9600

Gorte, B., Stein, A.,
Bayesian Classification and Class Area Estimation of Satellite Images Using Stratification,
GeoRS(36), No. 3, May 1998, pp. 803-812.
IEEE Top Reference. 9806 BibRef

Rajan, J.J., Rayner, P.J.W., Godsill, S.J.,
Bayesian Approach to Parameter Estimation and Interpolation of Time Varying Autoregressive Processes Using the Gibbs Sampler,
VISP(144), No. 4, August 1997, pp. 249-256. 9806 BibRef

Sanjaygopel, S., Hebert, T.J.,
Bayesian Pixel Classification Using Spatially Variant Finite Mixtures and the Generalized EM Algorithm,
IP(7), No. 7, July 1998, pp. 1014-1028.
IEEE DOI may work or IEEE-CS DOI may work. 9807 BibRef

Roberts, S.J.[Stephen J.], Husmeier, D.[Dirk], Rezek, I.[Iead], Penny, W.D.[William D.],
Bayesian Approaches to Gaussian Mixture Modeling,
PAMI(20), No. 11, November 1998, pp. 1133-1142.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9811 BibRef

Williams, C.K.I., Barber, D.,
Bayesian Classification With Gaussian Processes,
PAMI(20), No. 12, December 1998, pp. 1342-1351.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9812

Horiuchi, T.[Takahiko],
Decision Rule for Pattern Classification by Integrating Interval Feature Values,
PAMI(20), No. 4, April 1998, pp. 440-448.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9806 Bayes Nets. BibRef

Horiuchi, T.[Takahiko],
Pattern Classification Method by Integrating Interval Feature Values,
ICDAR97(Poste) 9708 BibRef

Warrender, C.E.[Christina E.], Augusteijn, M.F.[Marijke F.],
Fusion of image classifications using Bayesian techniques with Markov random fields,
JRS(20), No. 10, July 1999, pp. 1987. BibRef 9907

Foggia, P., Sansone, C., Tortorella, F., Vento, M.,
Multiclassification: reject criteria for the Bayesian combiner,
PR(32), No. 8, August 1999, pp. 1435-1447.
WWW Version. BibRef 9908

Cordella, L.P., Foggia, P., Sansone, C., Tortorella, F., Vento, M.,
Classification reliability and its use in multi-classifier systems,
CIAP97(I: 46-53).
WWW Version. 9709 BibRef

Foggia, P.[Pasquale], Percannella, G.[Gennaro], Sansone, C.[Carlo], Vento, M.[Mario],
Evaluating Classification Reliability for Combining Classifiers,
CIAP07(711-716).
IEEE DOI may work or IEEE-CS DOI may work. 0709 BibRef

Cordella, L.P., Foggia, P., Sansone, C., Vento, M.,
Learning structural shape descriptions from examples,
PRL(23), No. 12, October 2002, pp. 1427-1437.
HTML Version. 0206 BibRef

Marrocco, C.[Claudio], Molinara, M.[Mario], Tortorella, F.[Francesco],
Exploiting AUC for optimal linear combinations of dichotomizers,
PRL(27), No. 8, June 2006, pp. 900-907.
WWW Version. 0605 BibRef
Earlier:
AUC-Based Linear Combination of Dichotomizers,
SSPR06(714-722).
WWW Version. 0608 BibRef
Earlier:
Estimating the ROC Curve of Linearly Combined Dichotomizers,
CIAP05(778-785).
WWW Version. 0509Two-class classifiers; ROC curve; Multiple classifier systems; Linear combiners BibRef

Marrocco, C.[Claudio], Simeone, P.[Paolo], Tortorella, F.[Francesco],
A Framework for Multiclass Reject in ECOC Classification Systems,
SCIA07(313-323).
WWW Version. 0706 BibRef

Antos, A.[Andras], Devroye, L.[Luc], Gyoerfi, L.[Laszlo],
Lower Bounds for Bayes Error Estimation,
PAMI(21), No. 7, July 1999, pp. 643-645.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9907

Davis, R.[Robert], Prieditis, A.[Armand],
Designing Optimal Sequential Experiments for a Bayesian Classifier,
PAMI(21), No. 3, March 1999, pp. 193-201.
IEEE Abstract. IEEE Top Reference.
WWW Version. Generate better classifiers using more computation. BibRef 9903

Rangarajan, A.[Anand], Hsiao, I.T.[Ing-Tsung], Gindi, G.[Gene],
A Bayesian Joint Mixture Framework for the Integration of Anatomical Information in Functional Image Reconstruction,
JMIV(12), No. 3, June 2000, pp. 199-217.
WWW Version. 0003 BibRef

Rueda, L.G.[Luis G.], Oommen, B.J.[B. John],
On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case,
PAMI(24), No. 2, February 2002, pp. 274-280.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0202 Bayesian Clustering. Linear classifier is a pair of straight lines. BibRef

Rueda, L.G.[Luis G.], Oommen, B.J.[B. John],
On Optimal Pairwise Linear Classifiers for Normal Distributions: The D-Dimensional Case,
PR(36), No. 1, January 2003, pp. 13-23.
WWW Version. 0210 BibRef

Rueda, L.G.[Luis G.],
Selecting the best hyperplane in the framework of optimal pairwise linear classifiers,
PRL(25), No. 1, January 2004, pp. 49-62.
WWW Version. 0311 BibRef

Rueda, L.G.[Luis G.],
An efficient approach to compute the threshold for multi-dimensional linear classifiers,
PR(37), No. 4, April 2004, pp. 811-826.
WWW Version. 0403 BibRef

Rueda, L.G.[Luis G.],
A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes,
PR(38), No. 8, August 2005, pp. 1197-1207.
WWW Version. 0505 See also comment on: A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes by Rueda, A. BibRef

Oommen, B.J.[B. John], Rueda, L.G.[Luis G.],
Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments,
PR(39), No. 3, March 2006, pp. 328-341.
WWW Version. 0601 BibRef

Forsyth, D.A., Haddon, J., Ioffe, S.,
The Joy of Sampling,
IJCV(41), No. 1-2, January-February 2001, pp. 109-134.
WWW Version. Sampling for Bayesian models applied to structure from motion and color constancy.
WWW Version. 0105 BibRef

Huang, H.J.[Hung-Ju], Hsu, C.N.[Chun-Nan],
Bayesian classification for data from the same unknown class,
SMC-B(32), No. 2, April 2002, pp. 137-145.
IEEE Top Reference. 0205 BibRef

Zribi, M.[Mourad],
Non-parametric and unsupervised Bayesian classification with Bootstrap sampling,
IVC(22), No. 1, January 2004, pp. 1-8.
WWW Version. 0401 BibRef

Zribi, M.[Mourad],
Unsupervised Bayesian image segmentation using orthogonal series,
JVCIR(18), No. 6, December 2007, pp. 496-503.
WWW Version. 0711Unsupervised Bayesian image segmentation; Orthogonal series estimator; Stochastic and Nonparametric Expectation-Maximization BibRef

Zribi, M.[Mourad], Ghorbel, F.[Faouzi],
An Unsupervised and Non-Parametric Bayesian Classifier,
PRL(24), No. 1-3, January 2003, pp. 97-112.
HTML Version. 0211 BibRef
Earlier:
An unsupervised and non-parametric Bayesian Image segmentation,
CIAP95(423-428).
WWW Version. 9509 BibRef

Vass, G.G.[György G.], Daoudi, M.[Mohamed], Ghorbel, F.[Faouzi],
Optimization methods in multilayer classifier networks for automatic control of lamellibranch larva growth,
CIAP97(II: 220-227).
WWW Version. 9709 BibRef

Eastman, J.R., Laney, R.M.,
Bayesian Soft Classification for Sub-Pixel Analysis: A Critical Evaluation,
PhEngRS(68), No. 11, November 2002, pp. 1149-1154. Fuzzy training sites improve the accuracy of the Bayesian classification procedure by increasing the degree of overlap between parent distributions.
WWW Version. 0304 BibRef

Pernkopf, F.[Franz], O'Leary, P.[Paul],
Floating search algorithm for structure learning of Bayesian network classifiers,
PRL(24), No. 15, November 2003, pp. 2839-2848.
WWW Version. 0308 BibRef

Pernkopf, F.[Franz], O'Leary, P.[Paul],
Feature Selection for Classification Using Genetic Algorithms with a Novel Encoding,
CAIP01(161 ff.).
HTML Version. 0210 BibRef

Pernkopf, F.[Franz],
Bayesian network classifiers versus selective k-NN classifier,
PR(38), No. 1, January 2005, pp. 1-10.
WWW Version. 0410 BibRef

Raymer, M.L., Doom, T.E., Kuhn, L.A., Punch, W.F.,
Knowledge discovery in medical and biological datasets using a hybrid Bayes classifier/evolutionary algorithm,
SMC-B(33), No. 5, October 2003, pp. 802-813.
IEEE Abstract. IEEE Top Reference. 0310 BibRef

Thomaz, C.E., Gillies, D.F., Feitosa, R.Q.,
A New Covariance Estimate for Bayesian Classifiers in Biometric Recognition,
CirSysVideo(14), No. 2, February 2004, pp. 214-223.
IEEE Abstract. IEEE Top Reference. 0403 BibRef

Storvik, G., Fjortoft, R., Solberg, A.H.S.,
A Bayesian Approach to Classification of Multiresolution Remote Sensing Data,
GeoRS(43), No. 3, March 2005, pp. 539-547.
IEEE Abstract. IEEE Top Reference. 0501 BibRef

Kwoh, C.K.[Chee-Keong], Gillies, D.F.[Duncan Fyfe],
Estimating the initial values of unobservable variables in visual probabilistic networks,
CAIP95(326-333).
WWW Version. 9509 BibRef

Aksoy, S., Koperski, K., Tusk, C., Marchisio, G., Tilton, J.C.,
Learning Bayesian Classifiers for Scene Classification With a Visual Grammar,
GeoRS(43), No. 3, March 2005, pp. 581-589.
IEEE Abstract. IEEE Top Reference. 0501 BibRef

Jamain, A.[Adrien], Hand, D.J.[David J.],
The Naive Bayes Mystery: A classification detective story,
PRL(26), No. 11, August 2005, pp. 1752-1760.
WWW Version. 0506 BibRef

Zhang, H.[Harry], Su, J.[Jiang],
Learning probabilistic decision trees for AUC,
PRL(27), No. 8, June 2006, pp. 892-899.
WWW Version. Naive Bayes; Ranking 0605 BibRef

Nadarajah, S.[Saralees], Kotz, S.[Samuel],
A comment on: 'A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes' by Rueda,
PR(40), No. 5, May 2007, pp. 1632-1633.
WWW Version. 0702 See also one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes, A. BibRef

Shi, X.J.[Xiao-Jin], Manduchi, R.[Roberto],
On the Bayes fusion of visual features,
IVC(25), No. 11, 1 November 2007, pp. 1748-1758.
WWW Version. 0709Image classification; Bayes fusion; Color; Texture BibRef

Sicard, R.[Rudy], Artieres, T.[Thierry], Petit, E.[Eric],
Learning iteratively a classifier with the Bayesian Model Averaging Principle,
PR(41), No. 3, March 2008, pp. 930-938.
WWW Version. 0711Bayesian model averaging; Point estimate approximation; Naieve Bayes classifier; Statistical classification BibRef

Calvo, B.[Borja], Larranaga, P.[Pedro], Lozano, J.A.[Jose A.],
Learning Bayesian classifiers from positive and unlabeled examples,
PRL(28), No. 16, December 2007, pp. 2375-2384.
WWW Version. 0711Positive unlabeled learning; Bayesian classifiers; Naive Bayes; Tree augmented naive Bayes; Bayesian approach BibRef

Hernandez-Lobato, D.[Daniel], Hernandez-Lobato, J.M.[Jose Miguel],
Bayes Machines for binary classification,
PRL(29), No. 10, 15 July 2008, pp. 1466-1473.
WWW Version. 0711Kernel methods; Approximate inference; Bayesian methods; Expectation Propagation; Bayes Point Machines; Bayes Machines BibRef

Agrawal, R.K., Bala, R.[Rajni],
Incremental Bayesian classification for multivariate normal distribution data,
PRL(29), No. 13, 1 October 2008, pp. 1873-1876.
WWW Version. 0804Bayesian classification; Multivariate normal distribution; Sequential classification; Feature selection BibRef

Xuan, G.R.[Guo-Rong], Zhu, X.M.[Xiu-Ming], Shi, Y.Q.[Yun Q.], Chai, P.Q.[Pei-Qi], Cui, X.[Xia], Li, J.[Jue],
A Novel Bayesian Classifier with Smaller Eigenvalues Reset by Threshold Based on Given Database,
ICIAR07(375-386).
WWW Version. 0708 BibRef

Okatani, T.[Takayuki], Deguchi, K.[Koichiro],
Variational Bayes Based Approach to Robust Subspace Learning,
CVPR07(1-8).
IEEE DOI may work or IEEE-CS DOI may work. 0706 BibRef

Yuan, C.[Chao], Neubauer, C.[Claus],
A Variational Bayesian Approach for Classification with Corrupted Inputs,
CVPR07(1-8).
IEEE DOI may work or IEEE-CS DOI may work. 0706 BibRef

Phung, S.L.[Son Lam], Bouzerdoum, A., Chai, D., Watson, A.,
Naive bayes face/nonface classifier: a study of preprocessing and feature extraction techniques,
ICIP04(II: 1385-1388).
IEEE DOI may work or IEEE-CS DOI may work. 0505 BibRef

Jeon, Y.J.[Young-Joon], Choi, J.G.[Jae-Gark], Kim, J.I.[Jin-Il],
A Study on Supervised Classification of Remote Sensing Satellite Image by Bayesian Algorithm Using Average Fuzzy Intracluster Distance,
IWCIA04(597-606).
WWW Version. 0505 BibRef

Jermyn, I.H.[Ian H.],
On Bayesian Estimation in Manifolds,
INRIARR-4607, Octobre 2002.
HTML Version. 0306 BibRef

Mathis, C., Breuel, T.,
Classification using a hierarchical bayesian approach,
ICPR02(IV: 103-106).
IEEE DOI may work or IEEE-CS DOI may work. 0211 BibRef

Carvalho, P., Santos, A., Dourado, A., Ribeiro, B.,
Bayes information criterion for tikhonov regularization with linear constraints: application to spectral data estimation,
ICPR02(I: 696-700).
IEEE DOI may work or IEEE-CS DOI may work. 0211 BibRef

Keren, D.,
Painter identification using local features and naive bayes,
ICPR02(II: 474-477).
IEEE DOI may work or IEEE-CS DOI may work. 0211 BibRef

Qi, Y.[Yuan], Picard, R.W.,
Context-sensitive Bayesian classifiers and application to mouse pressure pattern classification,
ICPR02(III: 448-451).
IEEE DOI may work or IEEE-CS DOI may work. 0211 BibRef

Ling, L.L.[Lee Luan], Cavalcanti, H.M.,
Fast and Efficient Feature Extraction Based on Bayesian Decision Boundaries,
ICPR00(Vol II: 390-393).
IEEE DOI may work or IEEE-CS DOI may work.
HTML Version. 0009 BibRef

Sze, L., Leung, C.,
Branch and Bound Algorithm for the Bayes Classifier,
ICPR96(II: 705-709).
IEEE DOI may work or IEEE-CS DOI may work. 9608(Univ. of Hong Kong, HK) BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
K-Means Clustering .