Parameters optimization in r

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Parameters optimization in r

khan123
Hi

I will appreciate if someone provide the link to some tutorials/videos
where parameters running are performed in R. For instance, if we have to
perform predictions/classification using random forest or other algorithm,
how different optimization algorithms tune the parameters of random forest
such as numbers of trees etc.

Best regards

        [[alternative HTML version deleted]]

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Re: Parameters optimization in r

Bert Gunter-2
Google is your friend.



On Fri, Oct 11, 2019, 4:21 PM javed khan <[hidden email]> wrote:

> Hi
>
> I will appreciate if someone provide the link to some tutorials/videos
> where parameters running are performed in R. For instance, if we have to
> perform predictions/classification using random forest or other algorithm,
> how different optimization algorithms tune the parameters of random forest
> such as numbers of trees etc.
>
> Best regards
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: Parameters optimization in r

James Spottiswoode
In reply to this post by khan123
Hi,

I’ve often come across this problem and have found genetic algorithms (GA) to be extremely useful. I wrote my first GA code in the 80’s and have extensive experience with the method. The package rgenoud is a very full featured  GA implementation.  Just code up your parameters as arguments to the function giving your method, random forests or whatever, then define a target variable for performance or fitness such as AUC or R^2, whatever is appropriate, and let the GA climb to the top of the fitness landscape.  If you have a large problem you may want to speed things up by using parallel processes across cores or machines.  Rgenoud handles that well.

Good luck!

James


> On Oct 11, 2019, at 4:21 PM, javed khan <[hidden email]> wrote:
>
> Hi
>
> I will appreciate if someone provide the link to some tutorials/videos
> where parameters running are performed in R. For instance, if we have to
> perform predictions/classification using random forest or other algorithm,
> how different optimization algorithms tune the parameters of random forest
> such as numbers of trees etc.
>
> Best regards
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.