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.
|Author||Kevin R. Coombes|
|Bioconductor views||Clustering Microarray|
|Date of publication||2018-10-16 17:41:02|
|Maintainer||Kevin R. Coombes <[email protected]>|
|License||Apache License (== 2.0)|
|Package repository||View on R-Forge|
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