Detecting Novel Associations in Large Data Sets
Abstract
Identifying interesting relationships between pairs of variables in large data sets is increasingly important. Here, we present a measure of dependence for two-variable relationships: the maximal information coefficient (MIC). MIC captures a wide range of associations both functional and not, and for functional relationships provides a score that roughly equals the coefficient of determination (R(2)) of the data relative to the regression...
Paper Details
Title
Detecting Novel Associations in Large Data Sets
Published Date
Dec 16, 2011
Journal
Volume
334
Issue
6062
Pages
1518 - 1524
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