Re: [Dclib-devel] Multiclass classification
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Re: [Dclib-devel] Multiclass classification
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From: Mani A. <man...@gm...> - 2016-02-04 18:32:57
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Thanks! I also noticed there is a <b>one_vs_all</b> trainer
(<a class="moz-txt-link-freetext" href="http://dlib.net/ml.html#one_vs_all_trainer">http://dlib.net/ml.html#one_vs_all_trainer</a>)<br>
Isn't it more efficient and faster than <b>one_vs_one</b> trainer
for multiclass classification since it does not train N*(N-1)/2
binary classifiers.<br>
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- Mani<br>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">Subject: </th>
<td>Multiclass classification</td>
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<td>Wed, 3 Feb 2016 20:04:47 -0800</td>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">From: </th>
<td>Mani Amoozadeh <a class="moz-txt-link-rfc2396E" href="mailto:man...@gm..."><man...@gm...></a></td>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:dcl...@li...">dcl...@li...</a></td>
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inline !important; float: none;">I would try the
one_vs_one_trainer.=C2=A0 See=C2=A0 </span><a
href="=3D%22http://dlib.net/ml.html#one_vs_one_trainer%22"
style="font-family: 'Times New Roman'; font-size: medium;
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-webkit-text-stroke-width: 0px;"><a class="moz-txt-link-freetext" href="http://dlib.net/ml.html#one=">http://dlib.net/ml.html#one=</a>
_vs_one_trainer</a><br>
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<td>Multiclass classification</td>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">Date: </th>
<td>Wed, 3 Feb 2016 20:04:47 -0800</td>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">From: </th>
<td>Mani Amoozadeh <a class="moz-txt-link-rfc2396E" href="mailto:man...@gm..."><man...@gm...></a></td>
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<th nowrap="nowrap" valign="BASELINE" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:dcl...@li...">dcl...@li...</a></td>
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<p class="MsoNormal">Hi,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I am looking for a multiclass
classification algorithm in Dlib that can classify inputs into
three classes.<o:p></o:p></p>
<p class="MsoNormal">The inputs are 3-dimensional (x,y,z) and
like the following picture. After the training phase, the
algorithm<o:p></o:p></p>
<p class="MsoNormal">should be able to classify the input into
class 1,2 or 3.<br>
</p>
<p class="MsoNormal">Can you please give me a hint or show me a
skeleton example that I can start with?<o:p></o:p></p>
<p class="MsoNormal">Thanks!<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">- Mani<o:p></o:p></p>
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