Generalized random forests

Explore this paper's citation graph

Summary

A flexible, computationally efficient algorithm for growing generalized random forests, an adaptive weighting function derived from a forest designed to express heterogeneity in the specified quantity of interest, and an estimator for their asymptotic variance that enables valid confidence intervals are proposed.

Type
preprint
Published
2016-10-04
Cited by
1,809
References
114
Access
Open access

Keywords

Estimator, Weighting, Mathematics, Random forest, Curse of dimensionality

References

Cited by

Related papers