Performance Evaluation Metrics

Python 3

Theory

Confusion Matrix

		Actual value
		Positive	Negative
Predicted	Positive	True Positive	False Positive
Value	Negative	False Negative	True Negative

Accuracy

Precision

Precision is used when the cost of a false positive is higher than the cost of a false negative.

Recall

Recall is used when the cost of a false negative is higher than the cost false positive.

F1-Score

The F1-Score is an optimal blend of precision and recall.

Reference

https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html

https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html