Accuracy is the percentage of instances (evidence) correctly classified.

\( \frac{TP+ TN}{TP+ TN+ FP+ FN} \)

Recall is the percentage of instances that were correctly classified as positive.

\( \frac{TP}{TP+ FN} \)

Precision is the percentage of instances classified as positive (evidence) that are actually positive.

\( \frac{TP}{TP+ FP} \)

F Measure is the harmonic mean of precision and recall, meaning it combines the precision and recall.

\( \frac{2\ x\ precision\ \mathrm{x}\ recall}{precision+ recall} \)

Error Rate is the proportion of instances that are incorrectly classified.

\( \frac{FP+ FN}{TP+ FN+ FP+ TN} \)
