Published July 2, 2015
| Published
Journal Article
Open
Quantifying Redundant Information in Predicting a Target Random Variable
- Creators
- Griffith, Virgil
- Ho, Tracey
Chicago
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Abstract
We consider the problem of defining a measure of redundant information that quantifies how much common information two or more random variables specify about a target random variable. We discussed desired properties of such a measure, and propose new measures with some desirable properties.
Additional Information
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). Received: 18 March 2015; Accepted: 26 June 2015; Published: 2 July 2015. We thank Jim Beck, Yaser Abu-Mostafa, Edwin Chong, Chris Ellison, and Ryan James for helpful discussions. Author Contributions: Both authors shared in this research equally. Both authors have read and approved the final manuscript. Conflicts of Interest: The authors declare no conflict of interest.Attached Files
Published - entropy-17-04644.pdf
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entropy-17-04644.pdf
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Additional details
- Eprint ID
- 60177
- Resolver ID
- CaltechAUTHORS:20150910-140545452
- Created
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2015-09-11Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field