Random forest framework customized to handle highly correlated variables: an extensive experimental study applied to feature selection in genetic data.

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Contributor : Christine Sinoquet <>
Submitted on : Friday, January 18, 2019 - 11:40:11 PM
Last modification on : Tuesday, March 26, 2019 - 9:25:22 AM

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Christine Sinoquet, Kamel Mekhnacha. Random forest framework customized to handle highly correlated variables: an extensive experimental study applied to feature selection in genetic data.. IEEE 5th International Conference on Data Science and Advanced Analytics, DSAA2018, Oct 2018, Turin, Italy. pp.217-226. ⟨hal-01986653⟩

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