Chapter 6. Model Evaluation

Note

Learning Objectives

By the end of this chapter, you will be able to:

• Explain model evaluation, accuracy, null accuracy, and the limitations of accuracy

• Explain imbalanced datasets and confusion matrices

• Evaluate sensitivity, specificity, precision, FPR, ROC curves, and AUC scores

• Evaluate the classification threshold

Note

In this chapter, we will learn how to evaluate a model using accuracy. We will evaluate the model with sensitivity, specificity, precision, FPR, ROC curves, and AUC curves. Lastly, we will apply a classification threshold on the model.