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arXiv · 1608.02126

How Much Did it Rain? Predicting Real Rainfall Totals Based on Radar Data

Adam Lesnikowski
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Abstract

We applied a variety of parametric and non-parametric machine learning models to predict the probability distribution of rainfall based on 1M training examples over a single year across several U.S. states. Our top performing model based on a squared loss objective was a cross-validated parametric k-nearest-neighbor predictor that took about six days to compute, and was competitive in a world-wide competition.

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Adam Lesnikowski. 2016-08-06. How Much Did it Rain? Predicting Real Rainfall Totals Based on Radar Data. https://arxiv.org/abs/1608.02126

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