Comments (2)
Thanks for the question, @pawarbi! I can provide a little bit context on this
- Kats tsfeatures module provides 68 features while the tsfeatures Python package you shared has 22 features, so this differs a lot in terms of the numbers; also, when we started to develop this module (internally at facebook), there is no good feature extraction libraries in Python back then. Also, we're currently developing a neural network based approach for much faster and informative time series embeddings which we hope to release in our next release cycle.
- The R version is definitely great, and we also have contributors from the authors of the original paper and package so we're fully aware of the development.
- For performance comparison, we haven't dive into details but you're more than welcome to try our version on M3/M4 dataset and report back to the open source community, our team can also review the results afterwards!
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I'll close this issue since the question is resolved.
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