| meanFitness.BigBang {galgo} | R Documentation |
Computes the ``mean'' fitness from several solutions.
## S3 method for class 'BigBang': meanFitness(o, filter="none", subset=TRUE, ...)
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). If it is a numeric vector length one, a positive value means take those top chromosomes sorted by fitness, a negative value take those at bottom. |
The mean is built considering all solutions. For solutions that have finished earlier, the final fitness is used for futher genertions.
A vector with the mean fitness in each generation.
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
For more information see BigBang.
#bb is a BigBang object geneRankStability(bb)