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updated the docs
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<description>
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<p>
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Trains a <a href="#probabilistic_decision_function">probabilistic_decision_function</a> using
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some sort of trainer object such as the <a href="#svm_nu_trainer">svm_nu_trainer</a>.
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some sort of trainer object such as the <a href="#svm_nu_trainer">svm_nu_trainer</a> or
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<a href="#rbf_network_trainer">rbf_network_trainer</a>.
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</p>
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The probability model is created by using the technique described in the paper:
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<blockquote>
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<a href="#reduced_decision_function_trainer2">reduced_decision_function_trainer2</a>
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objects.
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</description>
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<examples>
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<example>svm_ex.cpp.html</example>
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</examples>
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</component>
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to further improve the results.
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</p>
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</description>
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<examples>
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<example>svm_ex.cpp.html</example>
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</examples>
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</component>
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<spec_file link="true">dlib/svm/svm_abstract.h</spec_file>
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<description>
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Performs k-fold cross validation on a user supplied trainer object such
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as the <a href="#svm_nu_trainer">svm_nu_trainer</a>.
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as the <a href="#svm_nu_trainer">svm_nu_trainer</a> or <a href="#rbf_network_trainer">rbf_network_trainer</a>.
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</description>
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<examples>
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<example>svm_ex.cpp.html</example>
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