HamzaG737/Deep-temporal-clustering
A non-official pytorch implementation of the DTC model for time series classification.
This helps researchers and analysts automatically categorize complex, multi-dimensional time series data without needing pre-labeled examples. You provide raw time series datasets, and it outputs organized groups or clusters of similar patterns, along with a performance score. It's designed for data scientists and researchers working with sensor data, medical signals, or financial trends.
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Use this if you have a large amount of unlabeled time series data and need to identify natural groupings or classify patterns automatically.
Not ideal if you already have labeled data for your time series and need a supervised classification model.
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55
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Language
Python
License
MIT
Category
Last pushed
Jun 20, 2021
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