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updated docs 

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Davis King 2010-12-23 23:11:34 +00:00
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23
docs/docs/ml.xml
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@ -77,6 +77,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>svm_c_ekm_trainer</item>
<item>rvm_trainer</item>
<item>krr_trainer</item>
<item>svr_trainer</item>
<item>rvm_regression_trainer</item>
<item>rbf_network_trainer</item>
<item>rank_features</item>
@ -919,6 +920,28 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>svr_trainer</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/svr_trainer_abstract.h</spec_file>
<description>
<p>
This object implements a trainer for performing epsilon-insensitive support
vector regression. It is implemented using the <a href="optimization.html#solve_qp3_using_smo">SMO</a> algorithm.
</p>
The implementation of the eps-SVR training algorithm used by this object is based
on the following paper:
<ul>
<li>Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector
machines, 2001. Software available at
<a href="http://www.csie.ntu.edu.tw/~cjlin/libsvm">http://www.csie.ntu.edu.tw/~cjlin/libsvm</a></li>
</ul>
</description>
</component>
<!-- ************************************************************************* -->
<component>

2
docs/docs/term_index.xml
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@ -172,6 +172,7 @@
<term file="ml.html" name="svm_c_ekm_trainer"/>
<term file="ml.html" name="rvm_trainer"/>
<term file="ml.html" name="krr_trainer"/>
<term file="ml.html" name="svr_trainer"/>
<term file="ml.html" name="rvm_regression_trainer"/>
<term file="ml.html" name="rbf_network_trainer"/>
<term file="ml.html" name="reduced"/>
@ -185,6 +186,7 @@
<term link="ml.html#svm_nu_trainer" name="support vector machine"/>
<term link="ml.html#rvm_trainer" name="relevance vector machine"/>
<term link="ml.html#krr_trainer" name="kernel ridge regression"/>
<term link="ml.html#svr_trainer" name="support vector regression"/>
<term link="ml.html#krr_trainer" name="regularized least squares"/>
<term link="ml.html#krr_trainer" name="least squares SVM"/>
<term file="ml.html" name="krls"/>