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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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DAWAK
2000
Springer
14 years 7 days ago
Mining Frequent Binary Expressions
In data mining, searching for frequent patterns is a common basic operation. It forms the basis of many interesting decision support processes. In this paper we present a new type ...
Toon Calders, Jan Paredaens
PADL
2000
Springer
13 years 11 months ago
Calculating a New Data Mining Algorithm for Market Basket Analysis
The general goal of data mining is to extract interesting correlated information from large collection of data. A key computationally-intensive subproblem of data mining involves ...
Zhenjiang Hu, Wei-Ngan Chin, Masato Takeichi
KDD
2002
ACM
145views Data Mining» more  KDD 2002»
14 years 8 months ago
Handling very large numbers of association rules in the analysis of microarray data
The problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for ...
Alexander Tuzhilin, Gediminas Adomavicius
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
TCBB
2010
176views more  TCBB 2010»
13 years 6 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...