标题： 因子化多类提升 显示英文标题

标题： Factorized MultiClass Boosting

摘要： 本文介绍了一种解决多类分类问题的新方法。我们将该问题分解为一系列回归任务，并用CART树来求解这些任务。所提出的方法比最先进的解决方案显著更快，同时提供了相同水平的模型质量。该算法对类别不平衡的数据集也很稳健，在不需要类别重新平衡的情况下，可以在更短的时间内达到高质量的结果。 显示英文摘要

摘要： 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.