Comments (2)
Hi, you will have to compute it manually. For example, this is how you can compute the mean and the standard deviation of the score of MLP on california (the same applies to ensembles and all other algorithms):
import json
import statistics
from pathlib import Path
scores = [
json.loads(x.joinpath('report.json').read_text())['metrics']['test']['score']
for x in Path('exp/mlp/california/0-evaluation').iterdir()
if x.is_dir()
]
print(f'{statistics.mean(scores)} +- {statistics.stdev(scores)}')
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OK! Thanks
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Related Issues (20)
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