GABi (version 0.1)

featureSelection.basic: Feature Selection for Block Biclusters in Binary Data

Description

A feature selection function for the GABi biclustering framework, based on the definition of a bicluster as a block of consistently high values across a submatrix within a binary dataset.

Usage

featureSelection.basic(cols)

Arguments

cols

Numeric vector representing a subset of the columns from x across which this solution's bicluster pattern is defined.

Value

x representing the maximal bicluster for the solution encoded by chr.

Details

A fast feature selection function is vital to the GABi framework of biclustering. In GABi, the bicluster problem is reformulated around the fact that each subset of the columns across a dataset will have one _maximal_ subset of rows that fit a specified pattern, and the submatrix defined by this maximal subset of rows will be the most interesting observation involving that subset of columns. Makes use of fitnessArgs a list of parameters in the environment of execution of the biclustering function GABi. Notably, the element consistency is used to apply a stringency threshold for selecting features (i.e. only those with the proportion of high values across the subset of samples being greater than consistency)