F-score

F-score is a way to measure how accurate something is. It looks at two different kinds of mistakes – when something is classified as correct, but it's actually wrong (called a False Positive) and when something is classified as wrong, but it's actually correct (called a False Negative). F-score adds up the number of False Positives and False Negatives, then divides this number by the total number of samples tested. The result is a score between 0 (all the samples were classified wrong) and 1 (all the samples were classified correctly). A higher F-score means that the accuracy of the samples is closer to 1, and a lower F-score means the accuracy is closer to 0.