Linear Approximation of F-Measure for the Performance Evaluation of Classification Algorithms on Imbalanced Data Sets

Accuracy is a popular measure for evaluating the performance of classification algorithms tested on ordinary data sets. When a data set is imbalanced, F-measure will be a better choice than accuracy for this purpose. Since F-measure is calculated as the harmonic mean of recall and precision, it is difficult to find the sampling distribution of F-m...