Conditional Super Learner

Gilmer Valdes; Yannet Interian; Efstathios D. Gennatas Mark J. Van der Laan

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arXiv · 1912.06675

Conditional Super Learner

Gilmer Valdes·Yannet Interian·Efstathios D. Gennatas Mark J. Van der Laan

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Abstract

In this article we consider the Conditional Super Learner (CSL), an algorithm which selects the best model candidate from a library conditional on the covariates. The CSL expands the idea of using cross-validation to select the best model and merges it with meta learning. Here we propose a specific algorithm that finds a local minimum to the problem posed, proof that it converges at a rate faster than $O_p(n^{-1/4})$ and offers extensive empirical evidence that it is an excellent candidate to substitute stacking or for the analysis of Hierarchical problems.

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BibTeX RIS

Gilmer Valdes, Yannet Interian, Efstathios D. Gennatas Mark J. Van der Laan. 2019-12-13. Conditional Super Learner. https://arxiv.org/abs/1912.06675

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