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Preprints, Working Papers, ... Year : 2014

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

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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Dates and versions

hal-00987803 , version 1 (06-05-2014)
hal-00987803 , version 2 (08-05-2014)

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Pierre Gaillard, Paul Baudin. A consistent deterministic regression tree for non-parametric prediction of time series. 2014. ⟨hal-00987803v2⟩
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