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Those methods still rely on correlation. To be clear: We are not only talking about linear correlation here, which is only one of several kinds of correlations.

• micro_cam 12y ago
  No they don't. They work directly with underlying estimates of probability distributions, entropy or impurity decrease in machine learning models. Another example: mendelian inheritance patterns in a pedigree study. If you know of a good measure of non linear correlation please let me know. And publish a paper in science or nature like the MIC/MINE people did (a measure that has issues in practice).
  • kretor 12y ago
    To estimate probability distributions, you need data that is non-random. Non-random means there's a pattern. That's another word for correlation. In using those methods you may never calculate correlation as a number, but when those methods find something you still rely on the fact that there is a correlation.