cauchyturing/UCR_Time_Series_Classification_Deep_Learning_Baseline

Fully Convlutional Neural Networks for state-of-the-art time series classification

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This project helps classify single-channel time series data from various domains by using deep learning. It takes raw time series as input and outputs a classification for each series, indicating what 'category' it belongs to. This is ideal for researchers or practitioners who need to quickly categorize temporal signals, such as identifying financial market patterns or recognizing health conditions from sensor data.

715 stars. No commits in the last 6 months.

Use this if you need a straightforward, end-to-end deep learning solution for classifying univariate time series and are looking for a strong baseline model with some interpretability features.

Not ideal if you prefer 'white box' models where you can easily understand the decision-making process, as traditional methods like BOSS might be more suitable in such cases.

time-series-classification financial-pattern-recognition industrial-monitoring healthcare-diagnostics signal-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 25 / 25

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Stars

715

Forks

207

Language

Python

License

Last pushed

Jul 03, 2019

Commits (30d)

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