Deep Transfer Learning Approaches in Performance Analysis of Brain Tumor Classification Using MRI Images

Table 1

Performance evaluation metrics for classification models [2].

Metrics	Formula	Evaluation focus
Accuracy (acc)		In general, the accuracy metric measures the ratio of correct predictions over the total number of instances evaluated.
Error rate (err)		Misclassification error measures the ratio of incorrect predictions over the total number of instances evaluated.
Sensitivity (sn)		This metric is used to measure the fraction of positive patterns that are correctly classified.
Specificity (sp)		This metric is used to measure the fraction of negative patterns that are correctly classified.
Precision (p)		Precision is used to measure the positive patterns that are correctly predicted from the total predicted patterns in a positive class.
Recall (r)		Recall is used to measure the fraction of positive patterns that are correctly classified.