Advances in Knowledge Discovery and Data Mining: 14th by Wei-Ying Ma (auth.), Mohammed J. Zaki, Jeffrey Xu Yu, B. PDF

By Wei-Ying Ma (auth.), Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, Vikram Pudi (eds.)

ISBN-10: 3642136567

ISBN-13: 9783642136566

This publication constitutes the lawsuits of the 14th Pacific-Asia convention, PAKDD 2010, held in Hyderabad, India, in June 2010.

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Extra resources for Advances in Knowledge Discovery and Data Mining: 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part I

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Clustering in ordered dissimilarity data. International Journal of Intelligent Systems 24(5), 504–528 (2009) 19. : Laplacian eigenmaps and spectral techniques for embedding and clustering. Advances in Neural Information Processing Systems 14, 585–591 (2002) 20. : Spectral graph theory. In: CBMS Regional Conference Series in Mathematics, American Mathematical Society, vol. 92 (1997) 21. : Self-tuning spectral clustering. Advances in Neural Information Processing Systems 17, 1601–1608 (2004) 22.

03 for DBE. We used both VAT and iVAT images to make our comparisons, and the results are summarized in Table 1, in which we used bold figures to show that the estimate is equal to the number of real physical classes cp and italic figures to show results that are relatively closer to cp . AAE and ARE represent average absolute error and average relative error between the number of estimated clusters and the number of real physical classes, respectively. From Table 1, it can be seen that: 1. , 2 correct and 2 closer for aVAT, 1 correct and 3 closer for CCE, and 2 closer to DBE).

In such cases, the Euclidean distance from the point x will be used as the projection distance. A “P artitionset” (denoted by Pi ) is defined as a set of datapoints which have lower projection distance to a particular component compared to the projection distance to any other component. A “P artition” is defined as a set of P artitionsets. Definition 1. (Nearest Component): Let dp ∈ D and P = {Pi } where Pi ’s are components, the nearest component of dp from P , denoted by N Comp(dp, P ), is defined as the component for which the projection distance from dp is minimum.

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Advances in Knowledge Discovery and Data Mining: 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part I by Wei-Ying Ma (auth.), Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, Vikram Pudi (eds.)


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