Mutual information between discrete and continuous data sets.
Mutual information (MI) is a powerful method for detecting relationships between data sets. There are accurate methods for estimating MI that avoid problems with "binning" when both data sets are discrete or when both data sets are continuous. We present an accurate, non-binning MI estimat...
Main Author: | Brian C Ross |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3929353?pdf=render |
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