Understanding AUC — ROC and Precision-Recall Curves

In this article, we will go through AUC ROC, and Precision-Recall curves concepts and explain how it helps in evaluating ML model’s performance. I would suggest you go through this Confusion Matrix post before you go ahead.

If you are actively preparing for a data science interview, this article will help you to answer the following questions:

1. What is the ROC curve?
2. What is the area under the curve?
3. What is the decision threshold in binary classification?
4. What AUC value is acceptable for a classification model?
5. What is the Precision-Recall curve?
6. When should you use precision-recall and ROC curves?

This article is part of a series where we walk step by step through solving fintech problems with different Machine Learning techniques using the “All lending club loan” dataset. Here you can find the complete end-to-end data science project for beginners to learn data science.

Introduction to Data Science with python: A complete guide to learn data science and machine…