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 [email protected]

GABi documentation built on May 1, 2019, 8:19 p.m.

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