Factorized MultiClass Boosting
Machine Learning
2019-09-12 v1 Machine Learning
Abstract
In this paper, we introduce a new approach to multiclass classification problem. We decompose the problem into a series of regression tasks, that are solved with CART trees. The proposed method works significantly faster than state-of-the-art solutions while giving the same level of model quality. The algorithm is also robust to imbalanced datasets, allowing to reach high-quality results in significantly less time without class re-balancing.
Cite
@article{arxiv.1909.04904,
title = {Factorized MultiClass Boosting},
author = {Igor E. Kuralenok and Yurii Rebryk and Ruslan Solovev and Anton Ermilov},
journal= {arXiv preprint arXiv:1909.04904},
year = {2019}
}