Online probabilistic label trees

Understand

We introduce online probabilistic label trees (OPLTs), an algorithm that trains a label tree classifier in a fully online manner without any prior knowledge about the number of training instances, their features and labels.

• OPLTs are characterized by low time and space complexity as well as strong theoretical guarantees.
• They can be used for online multi-label and multi-class classification, including the very challenging scenarios of one- or few-shot learning.
• We demonstrate the attractiveness of OPLTs in a wide empirical study on several instances of the tasks mentioned above.