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The reliability of analogy-based prediction

The reliability of analogy-based prediction This paper is focused on choosing a sufficient number of runs of a coupling Markov chain that makes it possible to generate, with a high confidence level, hypotheses such that at least one of them is inserted into any test example with high probability of positive prediction. The proposed technique is based on the Vapnik–Chervonenkis resampling method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Documentation and Mathematical Linguistics Springer Journals

The reliability of analogy-based prediction

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Allerton Press, Inc.
Subject
Computer Science; Information Storage and Retrieval
ISSN
0005-1055
eISSN
1934-8371
DOI
10.3103/S0005105517040033
Publisher site
See Article on Publisher Site

Abstract

This paper is focused on choosing a sufficient number of runs of a coupling Markov chain that makes it possible to generate, with a high confidence level, hypotheses such that at least one of them is inserted into any test example with high probability of positive prediction. The proposed technique is based on the Vapnik–Chervonenkis resampling method.

Journal

Automatic Documentation and Mathematical LinguisticsSpringer Journals

Published: Oct 1, 2017

References