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A Super-Learning Machine for Predicting Economic Outcomes

Cerulli, Giovanni (2020): A Super-Learning Machine for Predicting Economic Outcomes.

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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.

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