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» Benchmarking Data Mining Algorithms
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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 6 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
16 years 3 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
SISAP
2008
IEEE
175views Data Mining» more  SISAP 2008»
16 years 22 days ago
Anytime K-Nearest Neighbor Search for Database Applications
Many contemporary database applications require similarity-based retrieval of complex objects where the only usable knowledge of its domain is determined by a metric distance func...
Weijia Xu, Daniel P. Miranker, Rui Mao, Smriti R. ...
PAKDD
2009
ACM
94views Data Mining» more  PAKDD 2009»
15 years 11 months ago
Item Preference Parameters from Grouped Ranking Observations
Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
Hideitsu Hino, Yu Fujimoto, Noboru Murata
KDD
1999
ACM
185views Data Mining» more  KDD 1999»
15 years 10 months ago
Visual Classification: An Interactive Approach to Decision Tree Construction
Satisfying the basic requirements of accuracy and understandability of a classifier, decision tree classifiers have become very popular. Instead of constructing the decision tree ...
Mihael Ankerst, Christian Elsen, Martin Ester, Han...