Sensitive Error Correcting Output Codes
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چکیده
Sensitive error correcting output codes are a reduction from cost sensitive classi cation to binary classi cation. They are a modi cation of error correcting output codes [3] which satisfy an additional property: regret for binary classi cation implies at most 2 l2 regret for cost-estimation. This has several implications: 1) Any 0/1 regret minimizing online algorithm is (via the reduction) a regret minimizing online cost sensitive algorithm. In particular, this means that online learning can be made to work for arbitrary (i.e. totally unstructured) loss functions. 2) The output of the reduction can be thresholded so regret for binary classi cation implies at most 4 √ regret for cost sensitive classi caiton. 3) Using the canonical embeding of multiclass classifcation into cost sensitive classi cation, this reduction implies that binary regret implies at most 2 l2 error in the estimation of class probabilities. For a hard prediction, this implies at most 4 √ multiclass regret.
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