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» Classes and clusters in data analysis
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CMSB
2006
Springer
15 years 1 months ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
IJON
2008
173views more  IJON 2008»
14 years 10 months ago
Support vector machine classification for large data sets via minimum enclosing ball clustering
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...
Jair Cervantes, Xiaoou Li, Wen Yu, Kang Li
BIBE
2007
IEEE
155views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
Partial Mixture Model for Tight Clustering in Exploratory Gene Expression Analysis
Abstract—In this paper we demonstrate the inherent robustness of minimum distance estimator that makes it a potentially powerful tool for parameter estimation in gene expression ...
Yinyin Yuan, Chang-Tsun Li
FOCS
2000
IEEE
15 years 2 months ago
Clustering Data Streams
The data stream model has recently attracted attention for its applicability to numerous types of data, including telephone records, web documents and clickstreams. For analysis o...
Sudipto Guha, Nina Mishra, Rajeev Motwani, Liadan ...
ICPR
2010
IEEE
15 years 1 months ago
CDP Mixture Models for Data Clustering
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...
Yangfeng Ji, Tong Lin, Hongbin Zha