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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
15 years 6 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
AUSAI
2009
Springer
15 years 27 days ago
Adapting Spectral Co-clustering to Documents and Terms Using Latent Semantic Analysis
Abstract. Spectral co-clustering is a generic method of computing coclusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of ...
Laurence A. F. Park, Christopher Leckie, Kotagiri ...
BMCBI
2008
160views more  BMCBI 2008»
14 years 9 months ago
A comparison of four clustering methods for brain expression microarray data
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
ECML
2005
Springer
15 years 3 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu
KDD
2010
ACM
304views Data Mining» more  KDD 2010»
14 years 8 months ago
Automatic malware categorization using cluster ensemble
Malware categorization is an important problem in malware analysis and has attracted a lot of attention of computer security researchers and anti-malware industry recently. Today...
Yanfang Ye, Tao Li, Yong Chen, Qingshan Jiang