The randomized information coefficient: assessing dependencies in noisy data

DOI10.1007/S10994-017-5664-2zbMath1462.62362OpenAlexW2754601649WikidataQ56991808 ScholiaQ56991808MaRDI QIDQ1640393

Y. Aharonov

Publication date: 14 June 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-017-5664-2

zbMATH Keywords

dependency measuresnormalized mutual informationnoisy relationshipsrandomized ensembles

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Statistical aspects of information-theoretic topics (62B10)

Related Items (1)

Equitability, interval estimation, and statistical power

Uses Software

• SynTReN
• ARACNE
• MIDER
• JIDT
• RapidMic

Cites Work

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• Detecting Novel Associations in Large Data Sets
• Brownian distance covariance
• Measuring dependence powerfully and equitably
• Independent coordinates for strange attractors from mutual information
• Estimating Optimal Transformations for Multiple Regression and Correlation
• 10.1162/153244303322753616
• Algorithmic Learning Theory
• Extremely randomized trees
• Random forests

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