On-Line AdaTron Learning of Unlearnable Rules

Details On-Line AdaTron Learning of Unlearnable Rules On-Line AdaTron Learning of Unlearnable Rules

1997-03-03

arxiv.org/abs/cond-mat/9703019v1

Physics

Condensed Matter

RevTeX 17 pages, 8 figures, to appear in Phys.Rev.E

Scientific paper

10.1103/PhysRevE.55.4544

We study the on-line AdaTron learning of linearly non-separable rules by a simple perceptron. Training examples are provided by a perceptron with a non-monotonic transfer function which reduces to the usual monotonic relation in a certain limit. We find that, although the on-line AdaTron learning is a powerful algorithm for the learnable rule, it does not give the best possible generalization error for unlearnable problems. Optimization of the learning rate is shown to greatly improve the performance of the AdaTron algorithm, leading to the best possible generalization error for a wide range of the parameter which controls the shape of the transfer function.)

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