A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2004; you can also visit the original URL.
The file type is
The generalization performance of two learning algorithms, Bayes algorithm and the "optimal learning" algorithm, on two classification tasks is studied theoretically. In the first example the task is defined by a restricted two-layer network, a committee machine, and in the second the task is defined by the so-called prototype problem. The architecture of the learning machine, in both cases, is defined to be a committee machine. For both tasks the optimal learning algorithm, which is optimaldoi:10.1103/physreve.55.836 fatcat:zgtg6454n5g7hhiohueab7mmri