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JCB
2002
160views more  JCB 2002»
15 years 7 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
GFKL
2007
Springer
148views Data Mining» more  GFKL 2007»
16 years 1 months ago
Mixture Model Based Group Inference in Fused Genotype and Phenotype Data
The analysis of genetic diseases has classically been directed towards establishing direct links between cause, a genetic variation, and effect, the observable deviation of phenot...
Benjamin Georgi, M. Anne Spence, Pamela Flodman, A...
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
15 years 10 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
Cassio Pennachin, Moshe Looks, João A. de V...
ICDM
2006
IEEE
129views Data Mining» more  ICDM 2006»
16 years 1 months ago
Consensus Clustering for Detection of Overlapping Clusters in Microarray Data
Most clustering algorithms are partitional in nature, assigning each data point to exactly one cluster. However, several real world datasets have inherently overlapping clusters i...
Meghana Deodhar, Joydeep Ghosh
CIKM
2006
Springer
15 years 9 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu