tsflex
sspipe
| tsflex | sspipe | |
|---|---|---|
| 3 | 1 | |
| 361 | 145 | |
| 1.4% | 0.0% | |
| 6.3 | 0.0 | |
| 8 days ago | almost 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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tsflex
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[P] tsflex: flexible and efficient feature extraction for time series
tsflex its core functionality is strided-window feature extraction. This toolkit focusses on being flexible (e.g., few assumptions about sequence data, integration with other packages) and efficient (in both time & memory consumption -> see benchmark).
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Request - a good book for anomaly detection on time series
If you plan to transform your time series data in feature vectors, I would suggest to use tsflex (a rather new package) instead of TSfresh. tsflex is imo more convenient to use & multitudes more efficient for window-stride feature extraction.
sspipe
What are some alternatives?
tsfresh - Automatic extraction of relevant features from time series:
siuba - Python library for using dplyr like syntax with pandas and SQL
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
kindleServer - This project serve HTML files (and a few more) saved in your computer with a UI suitable for Kindle web browser. On top of that, it include a Read Mode (thanks to ReadabiliPy) to display the text in a comfortable size without have to use the 'Article Mode' in Kindle web browser.
MultiModalStory-demo - FairyTailor: Multimodal Generative Framework for Storytelling
concrete-numpy - Concrete-Numpy: A library to turn programs into their homomorphic equivalent.