Commit 55861855 authored by Davis King's avatar Davis King

updated the docs

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403316
parent 4f7551db
......@@ -123,6 +123,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<name>Miscellaneous</name>
<item>vector_normalizer</item>
<item>vector_normalizer_pca</item>
<item>discriminant_pca</item>
<item>randomize_samples</item>
<item>is_binary_classification_problem</item>
<item>test_binary_decision_function</item>
......@@ -323,6 +324,22 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<!-- ************************************************************************* -->
<component>
<name>discriminant_pca</name>
<file>dlib/statistics.h</file>
<spec_file link="true">dlib/statistics/dpca_abstract.h</spec_file>
<description>
This object implements the Discriminant PCA technique described in the paper:
<blockquote>
A New Discriminant Principal Component Analysis Method with Partial Supervision
by Dan Sun and Daoqiang Zhang
</blockquote>
</description>
</component>
<!-- ************************************************************************* -->
<component>
<name>vector_normalizer_pca</name>
<file>dlib/statistics.h</file>
......
......@@ -112,6 +112,7 @@
<term link="ml.html#mlp" name="neural network"/>
<term file="ml.html" name="svm_pegasos"/>
<term file="ml.html" name="empirical_kernel_map"/>
<term file="dlib/svm/empirical_kernel_map_abstract.h.html" name="empirical_kernel_map_error"/>
<term file="ml.html" name="kernel_matrix"/>
<term file="ml.html" name="batch"/>
<term file="ml.html" name="verbose_batch"/>
......@@ -139,6 +140,8 @@
<term file="ml.html" name="linearly_independent_subset_finder"/>
<term file="ml.html" name="vector_normalizer"/>
<term file="ml.html" name="vector_normalizer_pca"/>
<term file="ml.html" name="discriminant_pca"/>
<term file="dlib/statistics/dpca_abstract.h.html" name="discriminant_pca_error"/>
<term file="ml.html" name="kkmeans"/>
<term file="ml.html" name="pick_initial_centers"/>
<term file="ml.html" name="rank_features"/>
......
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