. 2022 Aug 28;11(17):2230. doi: 10.3390/plants11172230

Table 2.

Metric Equations and explanation.

Metric	Equation	Measure
Accuracy	$\frac{T_{P} + T_{N}}{T_{P} + T_{N} + F_{P}}$	A measure of the ratio of all correct classifications to the total number of the classifications
Precision	$\frac{T_{P}}{T_{P} + F_{P}}$	The ratio of the true positive cases over the total classified positive cases
Recall	$\frac{T_{P}}{T_{P} + F_{N}}$	(Sensitivity) The measure of the proportion of the actual positive cases that were classified correctly
Specificity	$\frac{T_{N}}{T_{N} + F_{P}}$	The measure of the proportion of the actual negative cases that were classified correctly
F1-Score	$\frac{2 T_{P}}{2 T_{P} + F_{P} + F_{N}}$	The harmonic mean of the precision and recall