July 2019
Beginner to intermediate
740 pages
16h 52m
English
Content preview from Hands-On Data Analysis with Pandas
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F score
The classification report also includes the F1 score, which helps us balance precision and recall using the harmonic mean of the two:
The harmonic mean is used for averaging rates. Both precision and recall are proportions on [0, 1], which we can treat as rates.
The Fβ score, pronounced F-beta, is the more general formulation for the F score. By varying β, we can put more weight on precision (β between 0 and 1) or on recall (β greater than 1), where β is how many more times recall is valued over precision:
Some commonly used values ...
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