Answer and Explanation:
Some of the advantages of using the F measure (weighted harmonic mean) over using the Precision & Recall when evaluating an IR system performance are as follows-
- Precision quantifies the number of positive class predictions that actually belong to the positive class.
- Recall quantifies the number of positive class predictions made out of all positive examples in the dataset.
- F-Measure provides a single score that balances both the concerns of precision and recall in one number.
- A measure that combines precision and recall is the harmonic mean of precision and recall, the traditional F-measure or balanced F-score:
F=2((precision.recall)/(precision+recall))
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B. all of those.
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