Quality metrics options #122
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added 7 commits
January 19, 2022 21:21
Tapot
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Jan 27, 2022
src/evidently/analyzers/prob_classification_performance_analyzer.py
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Tapot
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Jan 27, 2022
Tapot
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Jan 27, 2022
| average='macro') | ||
| avg_f1 = metrics.f1_score(reference_data[target_column], reference_data[prediction_column], | ||
| average='macro') | ||
| if len(prediction_column) > 2: |
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maybe will be better to set average='binary' or average='macro' depending on len(prediction_column) and set it explicitly in the same code for both cases?
Tapot
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Jan 27, 2022
| average='macro') | ||
| avg_f1 = metrics.f1_score(current_data[target_column], current_data[prediction_column], | ||
| average='macro') | ||
| if len(prediction_column) > 2: |
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the same as above, but for len(prediction_column)
This was referenced Feb 9, 2022
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Add quality metrics options:
conf_interval_n_sigmas
classification_threshold
cut_quantile