mirror of https://github.com/Relintai/pmlpp.git
368 lines
12 KiB
XML
368 lines
12 KiB
XML
<?xml version="1.0" encoding="UTF-8" ?>
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<class name="MLPPCost" inherits="Reference" version="3.11">
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<brief_description>
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</brief_description>
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<description>
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</description>
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<tutorials>
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</tutorials>
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<methods>
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<method name="cross_entropy_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="cross_entropy_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="cross_entropym">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="cross_entropyv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="dual_form_svm">
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<return type="float" />
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<argument index="0" name="alpha" type="MLPPVector" />
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<argument index="1" name="X" type="MLPPMatrix" />
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<argument index="2" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="dual_form_svm_deriv">
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<return type="MLPPVector" />
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<argument index="0" name="alpha" type="MLPPVector" />
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<argument index="1" name="X" type="MLPPMatrix" />
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<argument index="2" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="hinge_loss_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="hinge_loss_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="hinge_loss_derivwm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<argument index="2" name="C" type="float" />
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<description>
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</description>
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</method>
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<method name="hinge_loss_derivwv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<argument index="2" name="C" type="float" />
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<description>
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</description>
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</method>
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<method name="hinge_lossm">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="hinge_lossv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="hinge_losswm">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<argument index="2" name="arg2" type="MLPPMatrix" />
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<argument index="3" name="arg3" type="float" />
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<description>
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</description>
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</method>
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<method name="hinge_losswv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<argument index="2" name="arg2" type="MLPPVector" />
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<argument index="3" name="arg3" type="float" />
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<description>
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</description>
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</method>
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<method name="huber_loss_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<argument index="2" name="arg2" type="float" />
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<description>
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</description>
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</method>
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<method name="huber_loss_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<argument index="2" name="arg2" type="float" />
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<description>
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</description>
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</method>
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<method name="huber_lossm">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<argument index="2" name="arg2" type="float" />
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<description>
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</description>
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</method>
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<method name="huber_lossv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<argument index="2" name="arg2" type="float" />
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<description>
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</description>
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</method>
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<method name="log_loss_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="log_loss_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="log_lossm">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="log_lossv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="mae_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="mae_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="maem">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="maev">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="mbe_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="mbe_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="mbem">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="mbev">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="mse_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="mse_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="msem">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="msev">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="rmse_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="rmse_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="rmsem">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="rmsev">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="run_cost_deriv_matrix">
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<return type="MLPPMatrix" />
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<argument index="0" name="cost" type="int" enum="MLPPCost.CostTypes" />
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<argument index="1" name="y_hat" type="MLPPMatrix" />
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<argument index="2" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="run_cost_deriv_vector">
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<return type="MLPPVector" />
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<argument index="0" name="cost" type="int" enum="MLPPCost.CostTypes" />
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<argument index="1" name="y_hat" type="MLPPVector" />
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<argument index="2" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="run_cost_norm_matrix">
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<return type="float" />
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<argument index="0" name="cost" type="int" enum="MLPPCost.CostTypes" />
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<argument index="1" name="y_hat" type="MLPPMatrix" />
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<argument index="2" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="run_cost_norm_vector">
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<return type="float" />
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<argument index="0" name="cost" type="int" enum="MLPPCost.CostTypes" />
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<argument index="1" name="y_hat" type="MLPPVector" />
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<argument index="2" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="wasserstein_loss_derivm">
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<return type="MLPPMatrix" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="wasserstein_loss_derivv">
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<return type="MLPPVector" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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<method name="wasserstein_lossm">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPMatrix" />
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<argument index="1" name="y" type="MLPPMatrix" />
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<description>
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</description>
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</method>
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<method name="wasserstein_lossv">
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<return type="float" />
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<argument index="0" name="y_hat" type="MLPPVector" />
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<argument index="1" name="y" type="MLPPVector" />
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<description>
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</description>
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</method>
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</methods>
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<constants>
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<constant name="COST_TYPE_MSE" value="0" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_RMSE" value="1" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_MAE" value="2" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_MBE" value="3" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_LOGISTIC_LOSS" value="4" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_CROSS_ENTROPY" value="5" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_HINGE_LOSS" value="6" enum="CostTypes">
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</constant>
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<constant name="COST_TYPE_WASSERSTEIN_LOSS" value="7" enum="CostTypes">
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</constant>
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</constants>
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</class>
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