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||2016-05-09 21:26:32|
|Maintainer||Kevin R. Coombes <firstname.lastname@example.org>|
|License||Apache License (== 2.0)|
|Package repository||View on R-Forge|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.