Final answer:
The F-measure is a statistical measure used to evaluate the performance of a classification model. It combines both precision and recall into a single value.
Step-by-step explanation:
The F-measure is a statistical measure used to evaluate the performance of a classification model. It combines both precision and recall into a single value. The formula for calculating the F-measure is:
F-measure = 2 * (precision * recall) / (precision + recall)
To calculate the F-measure using the given confusion matrix, you need to know the values for true positives (TP), false positives (FP), and false negatives (FN). Once you have these values, you can plug them into the formula to get the F-measure.