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Default Metric Selection

# mkdocs_gallery_thumbnail_path = 'images/example_thumnail.png'

import numpy as np

from krisi import library, score

score(
    y=np.random.random(1000),
    predictions=np.random.random(1000),
    default_metrics=library.RegressionRegistry().all_regression_metrics,  # This is the default
).print()

score(
    y=np.random.random(1000),
    predictions=np.random.random(1000),
    default_metrics=library.RegressionRegistry().minimal_regression_metrics,
).print(input_analysis=False)

score(
    y=np.random.random(1000),
    predictions=np.random.random(1000),
    default_metrics=library.RegressionRegistry().low_computation_regression_metrics,
).print(input_analysis=False)

Total running time of the script: ( 0 minutes 0.000 seconds)

Download Python source code: evaluate_default_metric_selection.py

Download Jupyter notebook: evaluate_default_metric_selection.ipynb

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