Summary

This chapter explored the fascinating world of conformal predictors, their types, and their distinctive features. The key concepts and skills we touched upon include covering the foundational principles of conformal prediction and its application in machine learning. It also highlighted the differences between classical transductive and inductive conformal predictors. We also covered how to effectively choose the appropriate type of conformal predictor based on the specific requirements of the problem. Finally, the practical applications of conformal predictors in binary classification, multiclass classification, and regression were also included.

The chapter also provided a detailed algorithmic description and mathematical formulation of classical and inductive conformal predictors, adding to our theoretical understanding. To deepen our learning, we also took a hands-on approach, looking at practical examples in Python.

For those interested in further exploring conformal...