
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Kazunori Iwata, Akira Hayashi, "A RedundancyBased Measure of Dissimilarity among Probability Distributions for Hierarchical Clustering Criteria," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 1, pp. 7688, January, 2008.  
BibTex  x  
@article{ 10.1109/TPAMI.2007.1160, author = {Kazunori Iwata and Akira Hayashi}, title = {A RedundancyBased Measure of Dissimilarity among Probability Distributions for Hierarchical Clustering Criteria}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {30}, number = {1}, issn = {01628828}, year = {2008}, pages = {7688}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2007.1160}, 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  A RedundancyBased Measure of Dissimilarity among Probability Distributions for Hierarchical Clustering Criteria IS  1 SN  01628828 SP76 EP88 EPD  7688 A1  Kazunori Iwata, A1  Akira Hayashi, PY  2008 KW  clustering KW  mixture model KW  dissimilarity measure KW  information theory KW  Ward’s method VL  30 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
[1] E. Gokcay and J.C. Principle, “Information Theoretic Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 2, pp. 158171, Feb. 2002.
[2] U. Maulik and S. Bandyopadhyay, “Performance Evaluation of Some Clustering Algorithms and Validity Indices,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 12, pp. 16501654, Dec. 2002.
[3] M. Rosell, V. Kann, and J.E. Litton, “Comparing Comparisons: Document Clustering Evaluation Using Two Manual Classifications,” Proc. Int'l Conf. Natural Language Processing, pp. 207216, Dec. 2004.
[4] A.R. Webb, Statistical Pattern Recognition, second ed. John Wiley & Sons, 2002.
[5] R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, second ed. John Wiley & Sons, 2001.
[6] R. Xu and D.C. WunschII, “Survey of Clustering Algorithms,” IEEE Trans. Neural Networks, vol. 16, no. 3, pp. 645678, May 2005.
[7] T.W. Liao, “Clustering of Time Series Data—A Survey,” Pattern Recognition, vol. 38, no. 11, pp. 18571874, Nov. 2005.
[8] D. Yeung and X. Wang, “Improving Performance of SimilarityBased Clustering by Feature Weight Learning,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 4, pp. 556561, Apr. 2002.
[9] A.L. Fred and J.M. Leitão, “A New Cluster Isolation Criterion Based on Dissimilarity Increments,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 944958, Aug. 2003.
[10] M.S. Yang and K.L. Wu, “A SimilarityBased Robust Clustering Method,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 4, pp. 434448, Apr. 2004.
[11] M.E. Tipping, “Deriving Cluster Analytic Distance Functions from Gaussian Mixture Model,” Proc. Ninth Int'l Conf. Artificial Neural Networks, vol. 2, IEE, pp. 815820, Sept. 1999.
[12] M.S. Prieto and A.R. Allen, “A Similarity Metric for Edge Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 10, pp. 12651273, Oct. 2003.
[13] J. Wei, “Markov Edit Distance,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 3, pp. 311321, Mar. 2004.
[14] A. Srivastava, S.H. Joshi, W. Mio, and X. Liu, “Statistical Shape Analysis: Clustering, Learning, and Testing,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 4, pp. 590602, Apr. 2005.
[15] T. Kanungo, D.M. Mount, N.S. Netanyahu, C.D. Piatko, R. Silverman, and A.Y. Wu, “An Efficient KMeans Clustering Algorithm: Analysis and Implementation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 881892, July 2002.
[16] J.Z. Huang, M.K. Ng, H. Rong, and Z. Li, “Automated Variable Weighting in KMeans Type Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 5, pp. 657668, May 2005.
[17] C.J. Veenman, M.J. Reinders, and E. Backer, “A Maximum Variance Cluster Algorithm,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 12731280, Sept. 2002.
[18] F. Österreicher, “On a Class of PerimeterType Distances of Probability Distributions,” Cybernetics, vol. 32, no. 4, pp. 389393, 1996.
[19] F. Topsøe, “Some Inequalities for Information Divergence and Related Measures of Discrimination,” IEEE Trans. Information Theory, vol. 46, no. 4, pp. 16021609, July 2000.
[20] D.M. Endres and J.E. Schindelin, “A New Metric for Probability Distributions,” IEEE Trans. Information Theory, vol. 49, no. 7, pp.18581860, July 2003.
[21] T.S. Han and K. Kobayashi, Mathematics of Information and Coding, Translations of Math. Monographs, translated by J. Suzuki, vol.203, Am. Math. Soc., 2002.
[22] T.M. Cover and J.A. Thomas, Elements of Information Theory, Wiley Series in Telecommunications, first ed. John Wiley & Sons, 1991.
[23] S.J. Roberts, C. Holmes, and D. Denison, “MinimumEntropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 8, pp. 909914, Aug. 2001.
[24] I.N. Sanov, “On the Probability of Large Deviations of Random Variables,” Selected Translations in Math. Statistics and Probability, vol. 1, pp. 213244, 1961.
[25] A. Dembo and O. Zeitouni, Large Deviations Techniques and Applications, Applications of Math., second ed., vol. 38. Springer, 1998.
[26] J.H. Ward, “Hierarchical Grouping to Optimize an Objective Function,” J. Am. Statistical Assoc., vol. 58, no. 301, pp. 236244, 1963.
[27] J.H. Ward and M.E. Hook, “Application of an Hierarchical Grouping Procedure to a Problem of Grouping Profiles,” Educational Psychological Measurement, vol. 23, no. 1, pp. 6982, 1963.
[28] M.R. Anderberg, Cluster Analysis for Applications, Probability and Math. Statistics, vol. 19, Academic Press, 1973.
[29] P. Billingsley, Probability and Measure, Wiley Series in Probability and Math. Statistics, third ed. John Wiley & Sons, 1995.
[30] I. Csiszár and J. Körner, Information Theory: Coding Theorems for Discrete Memoryless Systems, first impression 1981, second impression 1986, third ed. Akadémiai Kiadó, 1997.
[31] J. Gärtner, “On Large Deviations from the Invariant Measure,” Theory of Probability and Its Applications, vol. 22, no. 1, pp. 2439, 1977.
[32] R.S. Ellis, “Large Deviations for a General Class of Random Vectors,” The Annals of Probability, vol. 12, no. 5, pp. 112, 1984.
[33] T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer Series in Statistics. Springer, 2001.
[34] C. Fraley, “Algorithms for ModelBased Gaussian Hierarchical Clustering,” SIAM J. Scientific Computing, vol. 20, no. 1, pp. 270281, Aug. 1998.
[35] M. Meilă and D. Heckerman, “An Experimental Comparison of ModelBased Clustering Methods,” Machine Learning, vol. 42, no. 1 and 2, pp. 929, Jan. 2001.
[36] D.J. Newman, S. Hettich, C.L. Blake, and C.J. Merz, UCI Repository of Machine Learning Databases, http://www.ics.uci.edu/~mlearnMLRepository.html , 1998.
[37] C.M. Bishop, Neural Networks for Pattern Recognition. Oxford Univ. Press, 1995.
[38] L. Devroye, L. Györfi, and G. Lugosi, A Probability Theory of Pattern Recognition, Applications of Math., vol. 31. Springer, 1996.