The Randomized Dependence Coefficient
Machine Learning
2013-06-04 v2
Abstract
We introduce the Randomized Dependence Coefficient (RDC), a measure of non-linear dependence between random variables of arbitrary dimension based on the Hirschfeld-Gebelein-R\'enyi Maximum Correlation Coefficient. RDC is defined in terms of correlation of random non-linear copula projections; it is invariant with respect to marginal distribution transformations, has low computational cost and is easy to implement: just five lines of R code, included at the end of the paper.
Cite
@article{arxiv.1304.7717,
title = {The Randomized Dependence Coefficient},
author = {David Lopez-Paz and Philipp Hennig and Bernhard Schölkopf},
journal= {arXiv preprint arXiv:1304.7717},
year = {2013}
}