filterSolution.BigBang: Filters solutions

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

Description

Filters solutions.

Usage

## S3 method for class 'BigBang'
filterSolution(o, filter=c("none", "solutions", "nosolutions"), subset, ...)

Arguments

filter	The BigBang object can save information about solutions that did not reach the goalFitness. filter=="solutions" ensures that only chromosomes that reach the goalFitness are considered. fitlter=="none" take all chromosomes. filter=="nosolutions" consider only no-solutions (for comparative purposes).
subset	Second level of filter. subset can be a vector specifying which filtered chromosomes are used. It can be a logical vector or a numeric vector (indexes in order given by $bestChromosomes in BigBang object variable).

Value

Returns a logical vector indicating which chromosomes are valid for the given filter.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see BigBang.

Examples

## Not run: 
   ok <- filterSolution(bb, filter="solutions", subset=1:100)
   sum(ok)
   
## End(Not run)
 

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