updated docs

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extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%404199
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Davis King 2011-03-24 02:44:44 +00:00
parent e11cf36f63
commit f6ddef170e
3 changed files with 19 additions and 1 deletions

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@ -77,6 +77,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<name>Multiclass Classification</name>
<item>one_vs_one_trainer</item>
<item>one_vs_all_trainer</item>
<item>svm_multiclass_linear_trainer</item>
</section>
<section>
<name>Regression</name>
@ -1300,6 +1301,21 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>svm_multiclass_linear_trainer</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/svm_multiclass_linear_trainer_abstract.h</spec_file>
<description>
This object represents a tool for training a multiclass support
vector machine. It is optimized for the case where linear kernels
are used and implemented using the <a href="optimization.html#structural_svm_problem">structural_svm_problem</a>
object.
</description>
</component>
<!-- ************************************************************************* -->
<component>

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@ -672,7 +672,8 @@ subject to the following constraint:
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/structural_svm_problem_abstract.h</spec_file>
<description>
This object is a tool for solving the optimization problem associated
This object, when used with the <a href="#oca">oca</a> optimizer, is a tool
for solving the optimization problem associated
with a structural support vector machine. A structural SVM is a supervised
machine learning method for learning to predict complex outputs. This is
contrasted with a binary classifier which makes only simple yes/no predictions.

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@ -132,6 +132,7 @@
<term file="ml.html" name="select_all_distinct_labels"/>
<term file="dlib/svm/multiclass_tools_abstract.h.html#find_missing_pairs" name="find_missing_pairs"/>
<term file="ml.html" name="svm_multiclass_linear_trainer"/>
<term file="ml.html" name="one_vs_one_trainer"/>
<term file="ml.html" name="one_vs_one_decision_function"/>
<term file="ml.html" name="multiclass_linear_decision_function"/>