generateRandomModels: Generates Random shorter models

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Evaluate random models using the specified gene indexes.

Usage

generateRandomModels(genes,  bigbang, 
size=trunc(length(genes)/2), n=100, 
fitnessFunc=bigbang$data$modelSelectionFunc,
models=FALSE, ...)

Arguments

genes	Original chromosome object (or numeric vector).
bigbang	The BigBang object to be used to call the fitness function.
size	Size of new random models.
n	Number of models
fitnessFunc	The fitness function used to evaluate the chromosomes. The default is the usage of bigbang$galgo$fitnessFunc.
models	Logical value.
...	Other parameters passed to fitnessFunc.

Value

If models==TRUE, a vector of resulted fitness for random models, otherwise a list with models (matrix, cols=models) and their fitness (vector) is returned.

Author(s)

Victor Trevino

See Also

BigBang.

Examples

## Not run: 
rm <- generateRandomModels(geneFrequency(bb,value="index")[1:50],bb,size=5,n=100,models=T)
rm

## End(Not run)

galgo documentation built on May 2, 2019, 4:20 a.m.