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Abstract: Forecasting has attracted a lot of research interest, with very successful methods for periodic time series. Here, we propose a fast, automated method to do non-linear forecasting, for both periodic as well as chaotic time series. We use the technique of delay coordinate embedding, which needs several parameters; our contribution is the automated way of setting these parameters, using the concept of `intrinsic dimensionality'. Our operational system has fast and scalable algorithms for... (Update)
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BibTeX entry: (Update)
@misc{ chakrabarti-largescale,
author = "Deepayan Chakrabarti and Christos Faloutsos",
title = "{F4}: {L}arge--Scale Automated Forecasting Using Fractals",
url = "citeseer.ist.psu.edu/chakrabarti02largescale.html" }
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