
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander, "Bayesian Clustering of Fuzzy Feature Vectors Using a QuasiLikelihood Approach," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 1, pp. 7485, January, 2009.  
BibTex  x  
@article{ 10.1109/TPAMI.2008.53, author = {Pekka Marttinen and Jing Tang and Bernard De Baets and Peter Dawyndt and Jukka Corander}, title = {Bayesian Clustering of Fuzzy Feature Vectors Using a QuasiLikelihood Approach}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {31}, number = {1}, issn = {01628828}, year = {2009}, pages = {7485}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.53}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Bayesian Clustering of Fuzzy Feature Vectors Using a QuasiLikelihood Approach IS  1 SN  01628828 SP74 EP85 EPD  7485 A1  Pekka Marttinen, A1  Jing Tang, A1  Bernard De Baets, A1  Peter Dawyndt, A1  Jukka Corander, PY  2009 KW  Bayesian clustering KW  quasilikelihood KW  fuzzy modeling KW  continuous data VL  31 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
[1] D. Hand and K. Yu, “Idiot's Bayes—Not So Stupid After All,” Int'l Statistical Rev., vol. 69, pp. 385399, 2001.
[2] R. Herbrich, T. Graepel, and C. Campbell, “Bayes Point Machines,” J. Machine Learning Research, vol. 1, pp. 245279, 2001.
[3] B. Krishnapuram, A. Hartemink, L. Carin, and M. Figueiredo, “A Bayesian Approach to Joint Feature Selection and Classifier Design,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, pp. 11051111, 2004.
[4] H.C. Kim and Z. Ghahramani, “Bayesian Gaussian Process Classification with the EMEP Algorithm,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, pp. 19481959, 2006.
[5] S. Lloyd, “Least Squares Quantization in PCM,” IEEE Trans. Information Theory, vol. 28, pp. 129137, 1982.
[6] X. Zhou, X. Wang, and E.R. Dougherty, “Binarization of Microarray Data on the Basis of a Mixture Model,” Molecular Cancer Therapeutics, vol. 2, pp. 679684, 2003.
[7] R. Kohavi and M. Sahami, “ErrorBased and EntropyBased Discretization of Continuous Features,” Proc. Second Int'l Conf. Knowledge Discovery and Data Mining, pp. 114119, 1996.
[8] J. Bernardo and A. Smith, Bayesian Theory. John Wiley & Sons, 1994.
[9] R. Wedderburn, “QuasiLikelihood Functions, Generalized Linear Models, and the GaussNewton Method,” Biometrika, vol. 61, pp.439447, 1974.
[10] J. Corander, M. Gyllenberg, and T. Koski, “Random Partition Models and Exchangeability for Bayesian Identification of Population Structure,” Bull. of Math. Biology, vol. 69, pp. 797815, 2007.
[11] R. Duda, P. Hart, and D. Stork, Pattern Classification, second ed. John Wiley & Sons, 2000.
[12] P. Marttinen, J. Corander, P. Törönen, and L. Holm, “Bayesian Search of Functionally Divergent Protein Subgroups and Their Function Specific Residues,” Bioinformatics, vol. 22, pp. 24662474, 2006.
[13] C. Robert and G. Casella, Monte Carlo Statistical Methods, second ed. Springer, 2005.
[14] S. Sisson, “Transdimensional Markov Chains: A Decade of Progress and Future Perspectives,” J. Am. Statistical Assoc., vol. 100, pp. 10771089, 2005.
[15] B. Jones, C. Carvalho, A. Dobra, C. Hans, C. Carter, and M. West, “Experiments in Stochastic Computation for HighDimensional Graphical Models,” Statistical Science, vol. 20, pp. 388400, 2005.
[16] K.B. Laskey and J.W. Myers, “Population Markov Chain Monte Carlo,” Machine Learning, vol. 50, pp. 175196, 2003.
[17] J. Corander, M. Gyllenberg, and T. Koski, “Bayesian Model Learning Based on a Parallel MCMC Strategy,” Statistics and Computing, vol. 16, pp. 355362, 2006.
[18] A. Gelman, J. Carlin, H. Stern, and D. Rubin, Bayesian Data Analysis. Chapman & Hall, 1996.
[19] B. De Baets and H. De Meyer, “TransitivityPreserving Fuzzification Schemes for CardinalityBased Similarity Measures,” European J. Operational Research, vol. 160, pp. 726740, 2005.
[20] B. De Baets, S. Janssens, and H. De Meyer, “On the Transitivity of a Parametric Family of CardinalityBased Similarity Measures,” Int'l J. Approximate Reasoning, in press, 2008.
[21] J. Nelder, “QuasiLikelihood and PseudoLikelihood Are Not the Same Thing,” J. Applied Statistics, vol. 27, pp. 10071011, 2000.
[22] R. Fisher, “Theory of Statistical Estimation,” Proc. Cambridge Philosophical Soc., vol. 22, pp. 700725, 1925.
[23] B. Ripley, Pattern Recognition and Neural Networks. Cambridge Univ. Press, 1996.
[24] L. Hubert and P. Arabie, “Comparing Partitions,” J. Classification, vol. 2, pp. 193218, 1985.
[25] P. Cheeseman and J. Stutz, “Bayesian Classification (AutoClass): Theory and Results,” Advances in Knowledge Discovery and Data Mining, U. Fayyad, G. PiatetskyShapiro, P. Smyth, and R.Uthurusamy, eds., MIT Press, pp. 153180, 1996.
[26] M.A. Upal and E.M. Neufeld, “Comparison of Unsupervised Classifiers,” Proc. ISIS Information, Statistics and Induction in Science, pp. 342353, Aug. 1996.
[27] B. Slabbinck, B. De Baets, P. Dawyndt, and P. De Vos, “GenusWide Bacillus Species Identification through Proper Artificial Neural Network Experiments on Fatty Acid Profiles,” Antonie van Leeuwenhoek, doi: 10.1007/s104820089229z, 2008.
[28] P. Dawyndt, M. Vancanneyt, C. Snauwaert, B. De Baets, H. De Meyer, and J. Swings, “Mining Fatty Acid Databases for Detection of Novel Compounds in Aerobic Bacteria,” J. Microbiological Methods, vol. 66, pp. 410433, 2006.
[29] J. Corander, P. Marttinen, and S. Mäntyniemi, “Bayesian Identification of Stock Mixtures from Molecular Marker Data,” Fishery Bull., vol. 104, pp. 550558, 2006.
[30] W. Jiang and X. Liu, “Consistent Model Selection Based on Parameter Estimates,” J. Statistical Planning and Inference, vol. 121, pp. 265283, 2004.
[31] W. Pan, “Model Selection in Estimating Equations,” Biometrics, vol. 57, pp. 529534, 2001.
[32] J. Nelder and D. Pregibon, “An Extended QuasiLikelihood Function,” Biometrika, vol. 74, pp. 221232, 1987.
[33] D. Ashlock, Evolutionary Computation for Modeling and Optimization. Springer, 2006.
[34] R. Neal, “Markov Chain Sampling Methods for Dirichlet Process Mixture Models,” Technical Report 9815, Univ. of Toronto, 1998.
[35] D. Gevers, P. Dawyndt, P. Vandamme, A. Willems, M. Vancanneyt, J. Swings, and P. De Vos, “Stepping Stones towards a New Prokaryotic Taxonomy,” Philosophical Trans. of the Royal Soc.B—Biological Sciences, vol. 361, pp. 19111916, 2006.