quinngroup / SciPy2019-demo

Demo for Scipy 2019

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SciPy2019-demo

Demo for Scipy 2019

Run the task.py file first. This produces the features and saves them as pickled files Run the train_features.py second. This gives options to run TPOT to find the optimal classifier. If not specified, the program defaults to training a RandomForest classifier

Review the argparse help strings to ensure all arguments are being passed. You will need to download the DTI data from ppmi-info.org. If needed data can be provided upon request to reproduce results.

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Demo for Scipy 2019


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