A fitness function for the GABi biclustering framework, based on the simple principle that the larger the dense submatrix, the more interesting it is to discover.

1 | ```
getFitnesses.basic(chr)
``` |

`chr` |
Numeric vector representing a GA solution to the biclustering problem (i.e. a subset of the columns from |

A fitness function is fundamental to the success of a GA. In this case, `getFitnesses.basic`

evaluates the desirability of biclusters by multiplying the number of columns from dataset `x`

(argument for function `GABi`

) that displaying a consistent block of `1`

s involving the features that are observed to fit this pattern. 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 value representing fitness score for the solution encoded by `chr`

.

Ed Curry e.curry@imperial.ac.uk

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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