What are the evaluation parameters considered in logistic regression?

Following are the evaluation parameters considered in logistic regression

Precision

Recall

F1-Score

ROC curve

All the above parameters are considered on positive and negative rates of the classes which are tabulated below

a)Precision: Precision is an evaluation measure which is the combination of relevant as well as retrieved items over the total number of retrieved results. It is basically used when the case of false positive prediction is high.

b)Recall: Recall is a measure when False negative is considered.

d)F1-Score: F1-Score is an evaluation technique that maintains a balance between precision and recall

d)ROC Curve: ROC or Receiver Operating Characteristic curve is a graphical representation that gives an idea between True Positive rate against False Positive Rate at various threshold values.