Related papers: Online probabilistic label trees

Online probabilistic label trees

URL: http://arxiv.org/abs/2007.04451v2
Date: Fri, 26 Mar 2021 14:50:58 GMT
Title: Online probabilistic label trees
Authors: Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczy\'nski
Abstract summary: 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.
Score: 5.694890215546457
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: 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.

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