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» Feature Subset Selection and Ranking for Data Dimensionality...
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75
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PRL
1998
132views more  PRL 1998»
14 years 11 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
72
Voted
CORR
2007
Springer
95views Education» more  CORR 2007»
14 years 11 months ago
Resampling methods for parameter-free and robust feature selection with mutual information
Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time...
Damien François, Fabrice Rossi, Vincent Wer...
BMCBI
2007
173views more  BMCBI 2007»
14 years 11 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
90
Voted
BMCBI
2008
109views more  BMCBI 2008»
14 years 11 months ago
MetaFIND: A feature analysis tool for metabolomics data
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Kenneth Bryan, Lorraine Brennan, Padraig Cunningha...
85
Voted
ISDA
2009
IEEE
15 years 6 months ago
Measures for Unsupervised Fuzzy-Rough Feature Selection
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
Neil MacParthalain, Richard Jensen