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raamana avatar raamana commented on August 25, 2024

Hi Mukish, thanks for using neuropredict, and reporting it works well and produces the figures. Just double checked the results, and it appears the latest release does not export the CSV files yet, but all you need is actually stored in the results_neuropredict.pkl file.

I'd work on adding on documentation on using that file shortly - but this is what you need to know:

there is a dictionary of input options and output results stored in results_neuropredict.pkl file, and it can be loaded easily with:

import pickle
with open('results_neuropredict.pkl', 'rb') as rf:
    results = pickle.load(rf)

which is a dictionary with the following keys:

results_to_save = ['_workflow_type', '_checkpointing',

the metrics you are looking for, such as accuracy etc, are available in this dictionary results['results'].metric_val

the misclassified samplet IDs are stored in the dictionary results['results'].misclfd_samplets

let me know if you have any other questions.

from neuropredict.

raamana avatar raamana commented on August 25, 2024

were you able to get what you need, @mukishchezian ?

from neuropredict.

mukishchezian avatar mukishchezian commented on August 25, 2024

from neuropredict.

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