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updated the docs
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<item>decision_function</item>
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<item>probabilistic_decision_function</item>
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<item>krls</item>
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<item>one_class</item>
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<item>kcentroid</item>
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</sub>
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</item>
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</section>
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<!-- ************************************************************************* -->
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<component>
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<name>one_class</name>
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<name>kcentroid</name>
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<file>dlib/svm.h</file>
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<spec_file link="true">dlib/svm/one_class_abstract.h</spec_file>
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<spec_file link="true">dlib/svm/kcentroid_abstract.h</spec_file>
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<description>
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This is an implementation of an online algorithm for recursively estimating the
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center of mass of a sequence of training points. It uses the sparsification technique
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centroid of a sequence of training points. It uses the sparsification technique
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described in the paper The Kernel Recursive Least Squares Algorithm by Yaakov Engel.
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<p>
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<term link="algorithms.html#vector" name="vector"/>
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<term link="algorithms.html#point" name="point"/>
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<term link="algorithms.html#krls" name="krls"/>
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<term link="algorithms.html#one_class" name="one_class"/>
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<term link="algorithms.html#kcentroid" name="kcentroid"/>
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<term link="dlib/svm/svm_abstract.h.html#maximum_nu" name="maximum_nu"/>
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