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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 8 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
JMLR
2010
165views more  JMLR 2010»
13 years 2 months ago
Feature Selection: An Ever Evolving Frontier in Data Mining
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao
PAKDD
2005
ACM
120views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Speeding-Up Hierarchical Agglomerative Clustering in Presence of Expensive Metrics
In several contexts and domains, hierarchical agglomerative clustering (HAC) offers best-quality results, but at the price of a high complexity which reduces the size of datasets ...
Mirco Nanni
TKDE
2010
251views more  TKDE 2010»
13 years 2 months ago
Exploring Correlated Subspaces for Efficient Query Processing in Sparse Databases
The sparse data is becoming increasingly common and available in many real-life applications. However, relative little attention has been paid to effectively model the sparse data ...
Bin Cui, Jiakui Zhao, Dongqing Yang
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
14 years 1 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh