Excess Error , Approximation Error , and Estimation Error
نویسنده
چکیده
Another question of interest concerns the behaviour of a learning algorithm in the infinite sample limit: as it receives more and more data, does the algorithm converge to an optimal prediction rule, i.e. does the generalization error of the learned function approach the optimal error? Recall that for a distribution D on X × Y and a loss ` : Y × Y→[0,∞), the optimal error w.r.t. D and ` is the lowest possible error achievable by any function h : X→Y: er D = inf h:X→Y erD[h] . (1)
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