[R] Solving Classification problems in R

[Prof Brian Ripley]

http://cran.r-project.org/web/views/MachineLearning.html for a task view 
you missed.

On 28/02/2014 17:10, Luca Cerone wrote:
> Thanks for the advices Sergio and Jean-Olivier.
> Of course I forgot, but I am interested in supervised classification!
> I'll go through the packages you suggested to me!
> Any ideas for Neural Networks and Random Forests instead?
>
> Luca Cerone
>
> Tel: +34 692 06 71 28
> Skype: luca.cerone
>
>
> On Fri, Feb 28, 2014 at 6:01 PM, JiHO <jo.lists at gmail.com> wrote:
>> Do you mean supervised or unsupervised classification.
>>
>> If supervised, I have had great success using gradient boosted
>> classification in package gbm. multinomial distribution will get you
>> multiple classes and it will select relevant predictors by itself
>> given the training data.
>>
>> Not sure about the customized cost functions
>>
>> Jean-Olivier Irisson
>> —
>> Université Pierre et Marie Curie
>> Laboratoire d'Océanographie de Villefranche
>> 181 Chemin du Lazaret 06230 Villefranche-sur-Mer
>> Tel: +33 04 93 76 38 04
>> Mob: +33 06 21 05 19 90
>> http://www.obs-vlfr.fr/~irisson/
>> Send me large files at: http://www.obs-vlfr.fr/~irisson/upload/
>>
>> On Fri, Feb 28, 2014 at 5:53 PM, Sergio Fonda <sergio.fonda99 at gmail.com> wrote:
>>> Focus on MASS, CCA and e1071 packages
>>> Brgds,
>>> Sergio
>>> Il 28/feb/2014 17:47 "Luca Cerone" <luca.cerone at gmail.com> ha scritto:
>>>
>>>> Dear all,
>>>> I would like some advices on R packages to solve classification problems.
>>>> I have tried to search among the Task views, but couldn't find anything.
>>>>
>>>> Can somebody recommend me some packages?
>>>>
>>>> Some of the features I am looking for:
>>>> - deal with multiple classes
>>>> - use customized cost functions
>>>> - perform features/predictors selection
>>>>
>>>> Any hint would be greatly appreciated,
>>>> thanks a lot in advance for the help!
>>>> Cheers,
>>>> Luca
>>>>
>>>> ______________________________________________
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>>>> http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>
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>>>
>>> ______________________________________________
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>>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595