Loss functions for classification: Difference between revisions

Revision as of 21:45, 2 December 2014

Revision as of 03:30, 4 December 2014

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'''Loss function surrogates for classification''' are specificcomputationally feasible [[loss functions]] designedrepresenting tothe approximateprice thewe preferredwill [[indicatorpay function]]for lossesinaccuracy desiredpredicting forf(x) misclassificationsin place of y in classification problems. <ref>{{cite doi|10.1162/089976604773135104}}</ref>

Loss

== Square Loss ==