Given that I have a dataset with some number of 1s (positives) and 0s (negatives), and the following two sets of precision and recall values:

Set A:

Positive precision: 0.51

Positive recall: 0.8

Negative precision: 0.9

Negative recall: 0.7

Set B:

Positive precision: 0.9

Positive recall: 0.4

Negative precision: 0.76

Negative recall: 0.95

How can I combine these results so I can end up with the maximum amount of true positives? For example, something like subtracting the set of 0's from Set A (which I know to be 90% precise) from the set of 0's of Set B (which I know to have 95% of all 0s) and have the remaining be the False Negatives (or the actual positives) ?


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