Using the Perceptron Algorithm to Find Consistent Hypotheses

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


[img] PDF
Download (101Kb)


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.

Item Type: Article
ISSNs: 0963548314692163
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science
ePrint ID: 259818
Accepted Date and Publication Date:
Date Deposited: 24 Aug 2004
Last Modified: 31 Mar 2016 14:01
Further Information:Google Scholar

Actions (login required)

View Item View Item

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics