TimeSeriesClustering: An extensible framework in Julia

Julia Submitted 10 July 2019Published 08 September 2019
Review

Editor: @danielskatz (all papers)
Reviewers: @jgoldfar (all reviews), @ahwillia (all reviews)

Authors

Holger Teichgraeber (0000-0002-4061-2226), Lucas Elias Kuepper (0000-0002-1992-310X), Adam R. Brandt (0000-0002-2528-1473)

Citation

Teichgraeber et al., (2019). TimeSeriesClustering: An extensible framework in Julia. Journal of Open Source Software, 4(41), 1573, https://doi.org/10.21105/joss.01573

@article{Teichgraeber2019, doi = {10.21105/joss.01573}, url = {https://doi.org/10.21105/joss.01573}, year = {2019}, publisher = {The Open Journal}, volume = {4}, number = {41}, pages = {1573}, author = {Holger Teichgraeber and Lucas Elias Kuepper and Adam R. Brandt}, title = {TimeSeriesClustering: An extensible framework in Julia}, journal = {Journal of Open Source Software} }
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unsupervised learning representative periods optimization machine learning time series

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ISSN 2475-9066