Chapter 2. Introduction toScikit-Learn and Model Evaluation

Note

Learning Objectives

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

• Explain the response variable

• Describe the implications of imbalanced data in binary classification

• Split data into training and testing sets

• Describe model fitting in scikit-learn

• Derive several metrics for binary classification

• Create an ROC curve and a precision-recall curve

Note

This chapter will conclude the initial exploratory analysis and present new tools to perform model evaluation.