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Learning Time Series Detection Models from Temporally Imprecise Labels

This is a python implementation of the weakly supervised learning framework for timeseries detection models presented in

Learning Time Series Detection Models from Temporally Imprecise Labels Roy Adams and Benjamin M Marlin. AISTATS 2017.

The model is implemented following the scikit-learn fit predict model. A usage example for toy data can be found in code/examples.py. Dependencies can be found in requirements.txt.

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