A fully automated periodicity detection in time series



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We recently presented a scientific paper during ECML PKDD Advanced Analytics and Learning on Temporal Data workshop part of the ECML-PKDD 2019 conference at Wurzburg, Germany.


"A fully automated periodicity detection in time series" by Tom Puech, Matthieu Boussard, Anthony D’Amato, and Gaëtan Millerand.

To generate good models, you need the good features. For instance, knowing precisely the various periodicities of your temporal data is crucial. Does the time of day has a recurrent impact ? Does it exhibits another, fancier, periodicity ? This is precisely what this paper solves, by providing a new algorithm to automatically extract those features from your time series.

Download the file to read the full paper.

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Google Cloud
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