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Using the Perceptron Algorithm to Find Consistent Hypotheses

Record type: Article

The perceptron learning algorithm yields quite naturally an algorithm for finding a linearly separable boolean function consistent with a sample of such a function. Using the idea of a specifying sample, we give a simple proof that this algorithm is not efficient, in general.

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Citation

Anthony, M. and Shawe-Taylor, J. (1993) Using the Perceptron Algorithm to Find Consistent Hypotheses Combinatorics, Probability and Computing, 2, pp. 385-387.

More information

Published date: 1993
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 259818
URI: http://eprints.soton.ac.uk/id/eprint/259818
PURE UUID: 5f961608-d236-4be0-9d1a-161aea429059

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Date deposited: 24 Aug 2004
Last modified: 18 Jul 2017 09:19

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Contributors

Author: M. Anthony
Author: J. Shawe-Taylor

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