Consistency of plug-in confidence sets for classification in semi-supervised learning

Understand

Confident prediction is highly relevant in machine learning; for example, in applications such as medical diagnoses, wrong prediction can be fatal.

• For classification, there already exist procedures that allow to not classify data when the confidence in their prediction is weak.
• This approach is known as classification with reject option.
• In the present paper, we provide new methodology for this approach.