Group for Research in Decision Analysis


Mixed Effects Random Forest for Clustered Data

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This paper presents an extension of the well known random forest method to the case of clustered data. The proposed "mixed effects random forest" method is implemented using a standard random forest algorithm within the framework of the expectation-maximization (EM) algorithm. The simulation results show that the proposed mixed effects random forest method provide substantial improvements over standard random forest when the random effects are non negligible.

, 18 pages