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What is Precision?

Precision measures the proportion of observations that the algorithm predicts to be positive that actually are positive labels. In general, precision is calculated by:

Precision = True Positives / (True Positives + False Positives)

Using an example:

Confusion Matrix

Precision = 150 / (150 + 60) = .714

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