Table B.1.

Evaluation metrics

S. no.	Metrics	Description
1	$\text{Accuracy}=\frac{\text{TP}+\text{TN}}{\text{TP}+\text{TN}+\text{FP}+\text{FN}}$	Ratio of number of correct prediction and total number of input samples
2	$\text{Precision}=\frac{\text{TP}}{\text{TP}+\text{FP}}$	It is the no. of correct positives divided by the predicted positives
3	$\text{Recall}=\frac{\text{TP}}{\text{TP}+\text{FN}}$	It is the no. of correct positives divided by total no. of true positives and false negatives
4	$\text{F}1-\text{score}=2\ast \left[\frac{\text{P}\times \text{R}}{\text{P}+\text{R}}\right]$	Harmonic mean between precision and recall
5	$\text{Specificity}=\frac{\text{TN}}{\text{TN}+\text{FP}}$	The proportion of actual negatives predicted as positives
6	$\text{Sensitivity}=\frac{\text{TP}}{\text{TP}+\text{FN}}$	The proportion of actual positives predicted as positives
7	Positive $\text{LHR}=\frac{\text{Sensitivity}}{100-\text{Specificity}}$ $\text{Negative LHR}=\frac{100-\text{Sensitivity}}{\text{Sepcificity}}$	LHR assess the goodness of fit of two competing statistical models based on their likelihoods

P precision, R recall, TP true positive, TN true negative, FP false positive, and FN false negative, LHR likelihood ratio