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updated docs
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davisking committed Jul 1, 2015
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19 changes: 18 additions & 1 deletion docs/docs/ml.xml
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Expand Up @@ -111,6 +111,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>pick_initial_centers</item>
<item>kkmeans</item>
<item>find_clusters_using_kmeans</item>
<item>find_clusters_using_angular_kmeans</item>
<item>nearest_center</item>
<item>newman_cluster</item>
<item>spectral_cluster</item>
Expand Down Expand Up @@ -357,7 +358,23 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<file>dlib/clustering.h</file>
<spec_file link="true">dlib/svm/kkmeans_abstract.h</spec_file>
<description>
This is just a simple linear kmeans clustering implementation.
This is a simple linear kmeans clustering implementation.
It uses Euclidean distance to compare samples.
</description>

</component>

<!-- ************************************************************************* -->

<component>
<name>find_clusters_using_angular_kmeans</name>
<file>dlib/clustering.h</file>
<spec_file link="true">dlib/svm/kkmeans_abstract.h</spec_file>
<description>
This is a simple linear kmeans clustering implementation.
To compare a sample to a cluster, it measures the angle between them
with respect to the origin. Therefore, it tries to find clusters
of points that all have small angles between each cluster member.
</description>

</component>
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1 change: 1 addition & 0 deletions docs/docs/term_index.xml
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Expand Up @@ -424,6 +424,7 @@
<term file="dlib/statistics/dpca_abstract.h.html" name="discriminant_pca_error" include="dlib/statistics.h"/>
<term file="ml.html" name="kkmeans" include="dlib/clustering.h"/>
<term file="ml.html" name="find_clusters_using_kmeans" include="dlib/clustering.h"/>
<term file="ml.html" name="find_clusters_using_angular_kmeans" include="dlib/clustering.h"/>
<term file="ml.html" name="nearest_center" include="dlib/clustering.h"/>
<term file="ml.html" name="newman_cluster" include="dlib/clustering.h"/>
<term file="ml.html" name="spectral_cluster" include="dlib/clustering.h"/>
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