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» Classification with reject option in gene expression data
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BMCBI
2005
190views more  BMCBI 2005»
14 years 9 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry
KDD
2004
ACM
142views Data Mining» more  KDD 2004»
15 years 9 months ago
Meta-classification of Multi-type Cancer Gene Expression Data
Massive publicly available gene expression data consisting of different experimental conditions and microarray platforms introduce new challenges in data mining when integrating m...
Benny Y. M. Fung, Vincent T. Y. Ng
ICPR
2004
IEEE
15 years 10 months ago
Feature Selection and Gene Clustering from Gene Expression Data
In this article we describe an algorithm for feature selection and gene clustering from high dimensional gene expression data. The method is based on measuring similarity between ...
D. Dutta Majumder, Pabitra Mitra
ICDE
2008
IEEE
195views Database» more  ICDE 2008»
15 years 10 months ago
Scalable Rule-Based Gene Expression Data Classification
Abstract-- Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (i...
Mark A. Iwen, Willis Lang, Jignesh M. Patel
ICTAI
2007
IEEE
15 years 3 months ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas