gaTourResults: Results of a Genetic Algorithm
In GenAlgo: Classes and Methods to Use Genetic Algorithms for Feature Selection
Description
Usage
Format
Source
Description
We ran a genetic algorithm to find the optimal 'fantasy' team for the
competition run by the Versus broadcasting network for the 2009 Tour
de France. In order to make the vignette run in a timely fashion,
we saved the results in this data object.
Usage
1
Format
There are four objects in the data file. The first is recurse, which
is an object of the GenAlg-class representing the final
generation. The other three objects are all numeric vector of length 1100:
diversity contains the average population diversity at each generation,
fitter contains the maximum fitness, and meanfit contains the
mean fitness.
Source
Kevin R. Coombes
GenAlgo documentation built on Oct. 16, 2020, 3:01 a.m.
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Description Usage Format Source
Description
We ran a genetic algorithm to find the optimal 'fantasy' team for the competition run by the Versus broadcasting network for the 2009 Tour de France. In order to make the vignette run in a timely fashion, we saved the results in this data object.
Usage
1 |
Format
There are four objects in the data file. The first is recurse, which
is an object of the GenAlg-class representing the final
generation. The other three objects are all numeric vector of length 1100:
diversity contains the average population diversity at each generation,
fitter contains the maximum fitness, and meanfit contains the
mean fitness.
Source
Kevin R. Coombes
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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