[R] Genetic algorithm for feature selection

[Rolf Wester]

Thank you very much for your reply. I found the information on your home 
page very useful.

What I want to do is a PLS regression of a data set with 60 features for 
calibration purposes. 
In order to optimize the performance of the calibration I have to find 
out what features to use
in the PLS regression. Although this is what PLS-regression does but I 
found some articles
(R. Leardi, "Genetic algorithms applied to feature selection in PLS 
regression: how and when
to use them", Chemometrics and Intelligent Laboratory Systems 41 (1998) 
195-207) that claim
that a genetic optimization algorithm applied to feature selection 
could  further improve the calibration.
I found Python code that does exactly this but although I'm much more 
experienced in programming
in Python I think it's probably better to use R for this task. So I'm 
going to implement the genetic
algorithm described in the papers by Leardi in R.

Regards

Rolf

Patrick Burns wrote:
> I don't know what you are trying to do exactly, but
> in case you don't find anything pre-built there is the
> 'Rgenoud' package for genetic optimization and also
> the 'genopt' function that you can get from S Poetry.
>
>
> Patrick Burns
> patrick at burns-stat.com
> +44 (0)20 8525 0696
> http://www.burns-stat.com
> (home of S Poetry and "A Guide for the Unwilling S User")
>
> Rolf Wester wrote:
>
>> Hi,
>>
>> I'm looking for a R-package that does feature selection for PLS using 
>> a genetic optimization algorithm.
>> I couldn't find one on CRAN and I wonder whether there is a free one. 
>> I would be very appreciative for any help.
>>
>> Regards
>>
>> Rolf
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>>  
>>
>
>


-- 
------------------------------------
# Dr. Rolf Wester
# Fraunhofer Institut f. Lasertechnik
# Steinbachstrasse 15, D-52074 Aachen, Germany.
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