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https://issues.apache.org/jira/browse/MATH-1563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17246596#comment-17246596
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Gilles Sadowski commented on MATH-1563:
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{quote}
I have already requested a formal approval from IBM.
Let me know if there is any other formalities regarding this.
{quote}
For any sizable contribution, you'll have to fill an "ICLA" (contributor
agreement).
If you must be formally authorized by your employer, you might also need to
have it provide a corporate agreement. Further information:
https://www.apache.org/licenses/contributor-agreements.html
bq. I would like to participate in this endeavour.
As said, you should also post to the project's ["dev"
ML|http://commons.apache.org/mail-lists.html] about your proposal to expand the
GA functionality. The creation of a new component must be approved by the
project's [PMC|https://www.apache.org/dev/pmc.html], and the ML is the forum
for "official" project-wide communication.
> Implementation of Adaptive Probability Generation Strategy for Genetic
> Algorithm
> --------------------------------------------------------------------------------
>
> Key: MATH-1563
> URL: https://issues.apache.org/jira/browse/MATH-1563
> Project: Commons Math
> Issue Type: Improvement
> Reporter: AVIJIT BASAK
> Priority: Major
>
> In Genetic Algorithm probability of crossover and mutation operation can be
> generated in an adaptive manner. Some experiment was done related to this and
> published in this article
> "https://www.ijcaonline.org/archives/volume175/number10/basak-2020-ijca-920572.pdf";.
> Currently Apache's API works on constant probability strategy. I would like
> to propose incorporation of rank based adaptive probability generation
> strategy as described in the mentioned article. This will improve the
> performance and robustness of the algorithm and would make this more suitable
> for use in higher dimensional problems like machine learning or deep learning.
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