Summary
In this book’s final chapter, we explored the intriguing domain of multi-class conformal prediction. We began by understanding the concept of multi-class classification, a prevalent scenario in ML where an instance can belong to one of many classes. This understanding is crucial for effectively applying conformal prediction techniques.
We then delved into the metrics used for evaluating multi-class classification problems. These metrics quantitatively measure our model’s performance and are vital for effective model evaluation and selection.
Finally, we learned how to apply conformal prediction to multi-class classification problems. This section provided practical insights and techniques to apply to your industrial applications directly.
By the end of this chapter, you should have gained valuable skills and knowledge in multi-class classification and how conformal prediction can be effectively applied to these problems. This knowledge will prove invaluable...
