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BMCBI
2008
104views more  BMCBI 2008»
15 years 2 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 2 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
KDD
2003
ACM
124views Data Mining» more  KDD 2003»
16 years 2 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...
ICML
2005
IEEE
16 years 2 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
ESANN
2004
15 years 3 months ago
Using Andrews Curves for Clustering and Sub-clustering Self-Organizing Maps
Abstract. The use of self-organizing maps to analyze data often depends on finding effective methods to visualize the SOM's structure. In this paper we propose a new way to pe...
Cesar García-Osorio, Jesús Maudes, C...