Some Novel Measurement on Exploring Large Data Sets Based on Multi-variables Mutual Information Theory

نویسندگان

  • CHAO LIU
  • David N. Reshef
چکیده

Applying for information theory, we present a measure of dependence for three-variable relationships: the three variables maximal information coefficient (3D-MIC). It is a kind of maximal information-based nonparametric exploration (MINE) statistics for identifying and classifying relationships in large data sets. 3D-MIC generalized the MIC measurement. At the same time some optimal single axis partition algorithm (OSPA) is built to ensure the feasibility of the MIC measurement.

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تاریخ انتشار 2013