Equitability, mutual information, and the maximal information coefficient
نویسندگان
چکیده
منابع مشابه
Equitability, mutual information, and the maximal information coefficient.
How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequa...
متن کاملTheoretical Foundations of Equitability and the Maximal Information Coefficient
The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables [1]. MIC is useful because it gives similar scores to equally noisy relationships of different types. This property, called equitability, is important for analyzing high-dimensional data sets. Here we formalize the theory behind both equitability and MIC in the ...
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A measure of dependence is said to be equitable if it gives similar scores to equally noisy relationships of different types. Equitability is important in data exploration when the goal is to identify a relatively small set of strongest associations within a dataset as opposed to finding as many non-zero associations as possible, which often are too many to sift through. Thus an equitable stati...
متن کاملCleaning up the record on the maximal information coefficient and equitability.
Although we appreciate Kinney and Atwal’s interest in equitability and maximal information coefficient (MIC), we believe they misrepresent our work. We highlight a few of our main objections below. Regarding our original paper (1), Kinney and Atwal (2) state “MIC is said to satisfy not just the heuristic notion of equitability, but also the mathematical criterion of R equitability,” the latter ...
متن کاملMutual Information Coefficient Analysis
In the domain of the Side Channel Attacks, various statistical tools have succeeded to retrieve a secret key, as the Pearson coefficient or the Mutual Information. In this paper we propose to study the Maximal Information Coefficient (MIC) which is a non-parametric method introduced by Reshef et al. [13] to compare two random variables. The MIC is based on the mutual information but it is easie...
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ژورنال
عنوان ژورنال: Proceedings of the National Academy of Sciences
سال: 2014
ISSN: 0027-8424,1091-6490
DOI: 10.1073/pnas.1309933111