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» Clustering functional data with the SOM algorithm
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CSDA
2007
99views more  CSDA 2007»
15 years 4 months ago
CLUES: A non-parametric clustering method based on local shrinking
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
Xiaogang Wang, Weiliang Qiu, Ruben H. Zamar
ICML
2003
IEEE
16 years 4 months ago
Learning Distance Functions using Equivalence Relations
We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
Aharon Bar-Hillel, Tomer Hertz, Noam Shental, Daph...
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
15 years 5 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
ESWA
2008
119views more  ESWA 2008»
15 years 4 months ago
Incremental clustering of mixed data based on distance hierarchy
Clustering is an important function in data mining. Its typical application includes the analysis of consumer's materials. Adaptive resonance theory network (ART) is very pop...
Chung-Chian Hsu, Yan-Ping Huang
TKDE
2012
245views Formal Methods» more  TKDE 2012»
13 years 6 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung