A consistent deterministic regression tree for non-parametric prediction of time series

Pierre Gaillard; Paul Baudin

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arXiv · 1405.1533

A consistent deterministic regression tree for non-parametric prediction of time series

Pierre Gaillard·Paul Baudin

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Abstract

We study online prediction of bounded stationary ergodic processes. To do so, we consider the setting of prediction of individual sequences and build a deterministic regression tree that performs asymptotically as well as the best L-Lipschitz constant predictors. Then, we show why the obtained regret bound entails the asymptotical optimality with respect to the class of bounded stationary ergodic processes.

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math.ST cs.LG stat.ML stat.TH

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BibTeX RIS

Pierre Gaillard, Paul Baudin. 2014-05-08. A consistent deterministic regression tree for non-parametric prediction of time series. https://arxiv.org/abs/1405.1533

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