Equitability Analysis of the Maximal Information Coefficient, with Comparisons

Understand

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 statistic, such as the maximal information coefficient (MIC), can be useful for analyzing high-dimensional data sets.
• Here, we explore both equitability and the properties of MIC, and discuss several aspects of the theory and practice of MIC.