Novelty detection

Novelty detection is the identification of new or unknown data that a machine learning system has not been trained with and was not previously aware of, with the help of either statistical or machine learning based approaches.

Novelty detection is one of the fundamental requirements of a good classification system. A machine learning system can never be trained with all the possible object classes and hence the performance of the network will be poor for those classes that are under-represented in the training set. A good classification system must have the ability to differentiate between known and unknown objects during testing. For this purpose, different models for novelty detection have been proposed.