A measure of machine learning model performance which measures the ability for a model to predict true negatives. Specificity is calculated as the true negative rate divided by the sum of the true negatives and the false positives. A specificity measure of 1 means that the model was able to detect all the true negatives without missing any that it has misclassified as a positive.
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