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autoTS: An automated machine learning for time series analysis

autoTS is an automated system for time series analysis that uses semnatic workflows to represent sophisticated methods and their constraints. AutoTs extends the WINGS workflow system with new capbilities to cutomize general methods to specific datasets based on key characteristics of the data.

The methods are encapsulated in the Pyleoclim package

This repository contains the following:

  • Notebooks the describe a certain methodology and workflow strategies
  • Sample data with know characteristics (e.g. periodicity, noise, amount of missing data) to test the methods and workflow strategies.
  • Code to automatically profile data (e.g. trend)

Further information

Fore more information about the project, visit our website.

Contact

Please report issues to khider@usc.edu

License

The material on this repository is licensed under the Apache 2.0 License.

Disclaimer

This research is funded by JP Morgan Chase & Co. Any views or opinions expressed herein are solely those of the authors listed, and may differ from the views and opinions expressed by JP Morgan Chase & Co. or its affilitates. This material is not a product of the Research Department of J.P. Morgan Securities LLC. This material should not be construed as an individual recommendation of for any particular client and is not intended as a recommendation of particular securities, financial instruments or strategies for a particular client. This material does not constitute a solicitation or offer in any jurisdiction.