A Super-Learning Machine for Predicting Economic Outcomes

Giovanni Cerulli

MPRA Paper from University Library of Munich, Germany

Abstract: We present a Super-Learning Machine (SLM) to predict economic outcomes which improves prediction (i) by cross-validated optimal tuning, (ii) by comparing/combining results from different learners. Our application to a labor economics dataset shows that different learners may behave differently. However, combining learners into one singleton super-learner proves to preserve good predictive accuracy lowering the variance more than stand-alone approaches.

Keywords: Machine learning; Ensemble methods; Optimal prediction (search for similar items in EconPapers)
JEL-codes: C53 C61 C63 (search for similar items in EconPapers)
Date: 2020-03-10
New Economics Papers: this item is included in nep-big, nep-cmp, nep-exp and nep-ore
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:99111

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