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Tag: metrics

SHAP import local_accuracy

I’m trying to test metrics from the shap library https://github.com/slundberg/shap/blob/master/shap/benchmark/metrics.py I tried calling metrics like this : But am always getting the error : Answer Try instead: Why? Inspecting package’s top level __init__.py you’ll find out the following commented line:

Macro VS Micro VS Weighted VS Samples F1 Score

In sklearn.metrics.f1_score, the f1 score has a parameter called “average”. What does macro, micro, weighted, and samples mean? Please elaborate, because in the documentation, it was not explained properly. Or simply answer the following: Why is “samples” best parameter for multilabel classification? Why is micro best for an imbalanced dataset? what’s the difference between weighted and macro? Answer The question

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