Breed: Create an ensemble of 'children' from a given generation of...
In stat243proj/GA: Appllies a modified genetic algorithm to some dataset, in order to assess what combination of predictor variables are best able to predict
Description
Usage
Arguments
Details
Examples
Description
Breed() takes a generation and its associated fitness data
in fitness.vec as input and produces a number of children equal to the number
of parents in generation. This function allows for a natural rate of
genetic mutation as set by prob.mutate.
Usage
1
Breed(generation, fitness.vec, prob.mutate)
Arguments
generation
A list of individual genomes or co-variate sets
fitness.vec
A vector of the fitness values for the input generation
prob.mutate
A natural rate of gene mutation determined in Select.R
or fixed by the user.
Details
Breed() returns a list of 'genomes' for each child.
Called from within Select()
Examples
1
\code{\link[GA]{CrossOverMutate}}
stat243proj/GA documentation built on May 15, 2019, 5:03 a.m.
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Description Usage Arguments Details Examples
Description
Breed() takes a generation and its associated fitness data
in fitness.vec as input and produces a number of children equal to the number
of parents in generation. This function allows for a natural rate of
genetic mutation as set by prob.mutate.
Usage
1 | Breed(generation, fitness.vec, prob.mutate)
|
Arguments
generation |
A list of individual genomes or co-variate sets |
fitness.vec |
A vector of the fitness values for the input |
prob.mutate |
A natural rate of gene mutation determined in |
Details
Breed() returns a list of 'genomes' for each child.
Called from within Select()
Examples
1 | \code{\link[GA]{CrossOverMutate}}
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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