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» Memetic Algorithms for Feature Selection on Microarray Data
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ICDM
2007
IEEE
161views Data Mining» more  ICDM 2007»
14 years 1 months ago
Experimental Comparison of Feature Subset Selection Methods
In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some fe...
Chulmin Yun, Jihoon Yang
JMLR
2012
11 years 10 months ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
CORR
2006
Springer
93views Education» more  CORR 2006»
13 years 7 months ago
Functional dissipation microarrays for classification
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...
BMCBI
2008
169views more  BMCBI 2008»
13 years 7 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
14 years 1 months ago
On Feature Selection through Clustering
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...