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@tveasey tveasey commented May 29, 2019

This implements the (refined) "maximal information coefficient" measure of the strength of the relationship between two variables and uses it to initialise feature sample probabilities for the boosted tree. It also puts in place a mechanism to restrict the features used, if there are insufficient training data, to those variables with the strongest relationship with dependent variable.

@tveasey tveasey requested a review from valeriy42 July 2, 2019 15:28
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Good job on implementing MICe! 👏 I have a number of comments which aim to improve readability.

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tveasey commented Jul 5, 2019

Thanks for the review @valeriy42! I think I've addressed all your comments. Can you take another look.

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LGTM. Good job!

@tveasey tveasey merged commit 8bfe832 into elastic:feature/regression Jul 5, 2019
@tveasey tveasey deleted the regression-tune-feature-weights branch July 5, 2019 12:06
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