Description Usage Arguments Details Value Author(s)
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.
1 | featureSelection.basic(cols)
|
cols |
Numeric vector representing a subset of the columns from |
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
)
Numeric vector representing the features (i.e. rows) from dataset x
representing the maximal bicluster for the solution encoded by chr
.
Ed Curry e.curry@imperial.ac.uk
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.