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List: wekalist
Subject: Re: [Wekalist] about knowledge flow
From: Hoai-Thu Vuong <thuvh87 () gmail ! com>
Date: 2012-10-22 8:02:24
Message-ID: CABBkmgr9JArWKpAkUELhLktyY+88RA=DmhpOWzKJq-TEfoaYew () mail ! gmail ! com
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Hi preeti aggarwal, have you seen semi-supervised yet, i think co-training
is suitable with you.
On Mon, Oct 22, 2012 at 2:32 PM, preeti aggarwal <pree_agg2002@yahoo.com>wrote:
> Hello All
> I asked before also about classification using clustering and vice verse.
> Please help me in the same as i have more unknown samples than known
> samples. How to know the class of those unknown sample with good efficiency.
>
> Hope to hear from you soon.
>
>
> *
> Kind Regards
> Preeti Aggarwal
> CSE Deptt.
> Univ. Instt. Of Engg. & Technology
> Panjab University
> Sector 25
> Chandigarh.*
> ------------------------------
> *From:* Mark Hall <mhall@pentaho.com>
> *To:* Weka machine learning workbench list. <
> wekalist@list.scms.waikato.ac.nz>
> *Sent:* Monday, October 22, 2012 12:53 PM
> *Subject:* Re: [Wekalist] about knowledge flow
>
> On 19/10/12 4:14 PM, Hoai-Thu Vuong wrote:
> > Dear all.
> >
> > According to the document of WEKA, if i use the knowledge flow with
> > template cross-validation, I can save models, each of these is learnt in
> > each fold. But could you please give me the way to retrieve the best
> > model, i mean the finally model after k-fold training. Thank for your
> > helping.
>
> Cross validation gives you an estimate of the error on future data. You
> would typically use all the available training data to produce the final
> model.
>
> Cheers,
> Mark.
>
>
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>
>
>
> _______________________________________________
> Wekalist mailing list
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>
>
--
Thu.
[Attachment #5 (text/html)]
Hi preeti aggarwal, have you seen semi-supervised yet, i think co-training is \
suitable with you.<br><br><div class="gmail_quote">On Mon, Oct 22, 2012 at 2:32 PM, \
preeti aggarwal <span dir="ltr"><<a href="mailto:pree_agg2002@yahoo.com" \
target="_blank">pree_agg2002@yahoo.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc \
solid;padding-left:1ex"><div><div style="font-size:12pt;font-family:garamond,new \
york,times,serif">Hello All<br>I asked before also about classification using \
clustering and vice verse. Please help me in the same as i have more unknown samples \
than known samples. How to know the class of those unknown sample with good \
efficiency.<br>
<br>Hope to hear from you soon.<br><div><span><br></span></div><div> \
</div><div><font color="#a8bed1" size="1"><b><div><font><b>Kind \
Regards</b></font></div>Preeti Aggarwal<br>CSE Deptt.<br>Univ. Instt. Of Engg. & \
Technology<br>
Panjab University<br>Sector 25<br>Chandigarh.</b></font><br></div> <div \
style="font-family:garamond,new york,times,serif;font-size:12pt"> <div \
style="font-family:times new roman,new york,times,serif;font-size:12pt"> <div \
dir="ltr">
<font face="Arial"> <hr size="1"> <b><span \
style="font-weight:bold">From:</span></b> Mark Hall <<a \
href="mailto:mhall@pentaho.com" target="_blank">mhall@pentaho.com</a>><br> \
<b><span style="font-weight:bold">To:</span></b> Weka machine learning workbench \
list. <<a href="mailto:wekalist@list.scms.waikato.ac.nz" \
target="_blank">wekalist@list.scms.waikato.ac.nz</a>> <br>
<b><span style="font-weight:bold">Sent:</span></b> Monday, October 22, 2012 12:53 \
PM<br> <b><span style="font-weight:bold">Subject:</span></b> Re: [Wekalist] about \
knowledge flow<br> </font> </div><div><div class="h5"> <br>
On 19/10/12 4:14 PM, Hoai-Thu Vuong wrote:<br>> Dear all.<br>> <br>> \
According to the document of WEKA, if i use the knowledge flow with<br>> template \
cross-validation, I can save models, each of these is learnt in<br>
> each fold. But could you please give me the way to retrieve the best<br>> \
model, i mean the finally model after k-fold training. Thank for your<br>> \
helping.<br><br>Cross validation gives you an estimate of the error on future data. \
You would typically use all the available training data to produce the final \
model.<br>
<br>Cheers,<br>Mark.<br><br><br></div></div>_______________________________________________<br>Wekalist \
mailing list<br>Send posts to: <a href="mailto:Wekalist@list.scms.waikato.ac.nz" \
target="_blank">Wekalist@list.scms.waikato.ac.nz</a><br>
List info and subscription status: <a \
href="https://list.scms.waikato.ac.nz/mailman/listinfo/wekalist" \
target="_blank">https://list.scms.waikato.ac.nz/mailman/listinfo/wekalist</a><br>List \
etiquette: <a href="http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html" \
target="_blank">http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html</a><br>
<br><br> </div> </div> \
</div></div><br>_______________________________________________<br> Wekalist mailing \
list<br> Send posts to: <a \
href="mailto:Wekalist@list.scms.waikato.ac.nz">Wekalist@list.scms.waikato.ac.nz</a><br>
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target="_blank">https://list.scms.waikato.ac.nz/mailman/listinfo/wekalist</a><br> \
List etiquette: <a href="http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html" \
target="_blank">http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html</a><br>
<br></blockquote></div><br><br clear="all"><div><br></div>-- <br>Thu.<br>
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