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List: wekalist
Subject: Re: [Wekalist] Auto Weka
From: javed khan <javedbtk111 () gmail ! com>
Date: 2019-05-17 0:55:12
Message-ID: CAJhui+tiW8_KQMhZu=yDJbcPUQ-cVzcpmGqQK0+A8X9xTT2m3A () mail ! gmail ! com
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Thanks, Eibe
It means, for ML algorithms (SVM) all the stuff will be provided by the
Auto Weka and for the meta-heuristic feature selection algorithms, we have
to manually set the parameters or stick with the default Weka parameters. I
think for feature selection algorithms, currently, it only supports
Best-First and Greedy Stepwise as described in [1].
[1] http://www.cs.ubc.ca/labs/beta/Projects/autoweka/papers/16-599.pdf
On Fri, May 17, 2019 at 12:21 AM Eibe Frank <eibe@waikato.ac.nz> wrote:
> Basically, yes. However, Auto-WEKA does not consider all algorithms in
> WEKA when it searches for a good solution. It has a specified set of
> algorithms that it considers during the search. I'm pretty sure SMO (for an
> SVM) is included, but I'm not sure about the genetic algorithm-based search
> for feature selection. It does have other feature selection methods in its
> collection though.
>
> Cheers,
> Eibe
>
> > On 16/05/2019, at 8:58 PM, javed khan <javedbtk111@gmail.com> wrote:
> >
> > Hello
> >
> > Is Auto Weka used to automatically adjust the parameters of various ML
> algorithms as well as the parameters of the feature selection algorithms?
> > For instance, if we use SVM and Genetic Search for a dataset NASA, then
> Auto Weka will adjust the best possible parameters? Is it so?
> >
> >
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>
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[Attachment #5 (text/html)]
<div dir="ltr">Thanks, Eibe<div><br></div><div>It means, for ML algorithms (SVM) all \
the stuff will be provided by the Auto Weka and for the meta-heuristic feature \
selection algorithms, we have to manually set the parameters or stick with the \
default Weka parameters. I think for feature selection algorithms, currently, it only \
supports Best-First and Greedy Stepwise as described in [1]. \
</div><div><br></div><div>[1] <a \
href="http://www.cs.ubc.ca/labs/beta/Projects/autoweka/papers/16-599.pdf">http://www.cs.ubc.ca/labs/beta/Projects/autoweka/papers/16-599.pdf</a> \
</div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, \
May 17, 2019 at 12:21 AM Eibe Frank <<a \
href="mailto:eibe@waikato.ac.nz">eibe@waikato.ac.nz</a>> \
wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px \
0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Basically, yes. \
However, Auto-WEKA does not consider all algorithms in WEKA when it searches for a \
good solution. It has a specified set of algorithms that it considers during the \
search. I'm pretty sure SMO (for an SVM) is included, but I'm not sure about the \
genetic algorithm-based search for feature selection. It does have other feature \
selection methods in its collection though.<br> <br>
Cheers,<br>
Eibe<br>
<br>
> On 16/05/2019, at 8:58 PM, javed khan <<a href="mailto:javedbtk111@gmail.com" \
target="_blank">javedbtk111@gmail.com</a>> wrote:<br> > <br>
> Hello<br>
> <br>
> Is Auto Weka used to automatically adjust the parameters of various ML \
algorithms as well as the parameters of the feature selection algorithms?<br> > \
For instance, if we use SVM and Genetic Search for a dataset NASA, then Auto Weka \
will adjust the best possible parameters? Is it so?<br> > <br>
> <br>
> _______________________________________________<br>
> Wekalist mailing list<br>
> Send posts to: <a href="mailto:Wekalist@list.waikato.ac.nz" \
target="_blank">Wekalist@list.waikato.ac.nz</a><br> > To subscribe, unsubscribe, \
etc., visit <a href="https://list.waikato.ac.nz/mailman/listinfo/wekalist" \
rel="noreferrer" target="_blank">https://list.waikato.ac.nz/mailman/listinfo/wekalist</a><br>
> List etiquette: <a \
href="http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html" \
rel="noreferrer" target="_blank">http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html</a><br>
<br>
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</blockquote></div>
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