Predictive Hypothesis Identification
نویسنده
چکیده
Canberra, ACT, 0200, Australia http://www.hutter1.net/ Summary • If prediction is the goal, but full Bayes not feasible, one should Identify (estimate/test/select) the Hypothesis (parameter/model/ interval) that Predicts best (PHI). •What best is can depend on benchmark (Loss, Lõss), distance function (d), how long we use the model (m), compared to how much data we have at hand (n). •The new principle (PHI) possesses many desirable properties. • In particular, PHI can properly deal with nested hypotheses, and nicely justifies, reconciles, and blends MAP and ML for m À n, MDL for m ≈ n, and SMF for n À m. NICTA
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عنوان ژورنال:
- CoRR
دوره abs/0809.1270 شماره
صفحات -
تاریخ انتشار 2008