10 - 704 : Information Processing and Learning Fall 2016 Lecture 11 : Oct 5

نویسنده

  • Aarti Singh
چکیده

In many machine learning task, we have data Z from some distribution p and the task is to minimize the risk: R(f) = EZ∼p[`(f(Z), Z)] (11.1) where ` is a loss function of interest, e.g. in classification Z = (X,Y ) and we use 0/1 loss `(f(Z), Z) = 1f(X)6=Y , in regression Z = (X,Y ) and we use squared error `(f(Z), Z) = (f(X) − Y ) and in density estimation Z = X and we use negative log likelihood loss `(f(Z), Z) = − log f(X). We are interested in finding the optimal predictor f∗ = arg min f R(f)

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تاریخ انتشار 2016