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Project based on the paper 'Deep Neural Network Ensembles for Time Series Classification' (2019)

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ProjectTimeSeriesClassificationUniUlm/EnsembleBasedTSC

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EnsembleBasedTSC

Project based on the paper Deep Neural Network Ensembles for Time Series Classification (2019) by Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Muller

Project Structure

The project uses Jupyter notebooks which combine the python sources.

File Description
Ensemble.py Provides the Ensemble class which allows combining trained models into an ensemble
Ensemblebuilder.py Provides methods to evaluate multiple Ensembles
Evaluation.py Provides helper methods to display results
Helpers.py Provides useful methods
LoadData.py Provides methods to load the datasets
ModelBuilder.py Provides methods that create keras models
PreprocessData.py Provides means to add noise to datasets
TrainProdecure.py Provides methods to train models

Usage

Install requirements and run the respective Jupyter notebook

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Project based on the paper 'Deep Neural Network Ensembles for Time Series Classification' (2019)

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