The DOI matches its Crossref record.
Information gain and a general measure of correlation
Abstract
Given a parametric model of dependence between two random quantities, X and Y, the notion of information gain can be used to define a measure of correlation. This definition of correlation generalizes both the usual product-moment correlation coeffi cient for the bivariate normal model and the multiple correlation coefficient in the standard linear regression model. The use of this information-based correlation in a descriptive statistical analysis is examined and several examples are given.
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Cited by
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Liu, S., See, K. C., Ngiam, K. Y., Celi, L. A., Sun, X., & Feng, M. (2020) · Journal of Medical Internet Research · doi:10.2196/18477 · Cited by 225
Gobert, J. D., Sao Pedro, M., Raziuddin, J., & Baker, R. S. (2013) · Journal of the Learning Sciences · doi:10.1080/10508406.2013.837391 · Cited by 210
How to Address the Data Quality Issues in Regression Models: A Guided Process for Data Cleaning
Corrales, D., Corrales, J., & Ledezma, A. (2018) · Symmetry · doi:10.3390/sym10040099 · Cited by 58
Wu, T., Weld, D. S., & Heer, J. (2019) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3319616 · Cited by 39
Metadata
- Authors
- KENT, J. T.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1983
- Volume
- 70
- Issue
- 1
- Pages
- 163-173
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2051725773
- Cited by
- 412
- References
- 0
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- closed
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- KENT, J. T. (1983). Information gain and a general measure of correlation. Biometrika. https://doi.org/10.1093/biomet/70.1.163
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