Classes and Methods to Use Genetic Algorithms for Feature Selection

Defines classes and methods that can be used to implement genetic algorithms for feature selection. The idea is that we want to select a fixed number of features to combine into a linear classifier that can predict a binary outcome, and can use a genetic algorithm heuristically to select an optimal set of features.


News

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*	       2.1 SERIES NEWS			 *
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	CHANGES IN R VERSION 2.1.5

MAINTENANCE

o	Cleaned up Depends, Imports and Suggests.
o	Fixed NAMESPACE issues.
o	Updated man pages and vignette.
o	Fixed encoding issues with te vignette, which includes
    non-ASCII UTF-8 characters (in people's names).

	CHANGES IN R VERSION 2.1.0

ADMINISTRATIVE

o	Changed LICENSE to Apache 2.0

	CHANGES IN R VERSION 2.0.1

BUG FIXES

o	Made compatible with new R check steps that verify DESCRIPTION
    and NAMESPACE dependencies.


	CHANGES IN R VERSION 2.0.0

REFACTOR

o	Removed depence on PreProcess.


	CHANGES IN R VERSION 1.0.3

RENAME!

o	Changed package name from GenAlg to GenAlgo to avoid a
conflict with an existing CRAN package.


	CHANGES IN R VERSION 1.0.2

BUG FIXES

o	Lots of documentation updates.


	CHANGES IN R VERSION 1.0.1

BUG FIXES

o	No clue...


	CHANGES IN R VERSION 1.0.0

NEW FEATURES

o	Brand new packaging: split out from the ClassPrediction
package, which is being restructured as a poor man's bundle
(i.e., no code, just some "depends" rules).

Reference manual

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install.packages("GenAlgo")

2.1.5 by Kevin R. Coombes, 10 months ago


http://oompa.r-forge.r-project.org/


Browse source code at https://github.com/cran/GenAlgo


Authors: Kevin R. Coombes


Documentation:   PDF Manual  


Apache License (== 2.0) license


Imports methods, stats, MASS, oompaBase, ClassDiscovery

Suggests Biobase, xtable


See at CRAN