Neural Regression Trees
Machine Learning
2020-02-13 v2 Machine Learning
Abstract
Regression-via-Classification (RvC) is the process of converting a regression problem to a classification one. Current approaches for RvC use ad-hoc discretization strategies and are suboptimal. We propose a neural regression tree model for RvC. In this model, we employ a joint optimization framework where we learn optimal discretization thresholds while simultaneously optimizing the features for each node in the tree. We empirically show the validity of our model by testing it on two challenging regression tasks where we establish the state of the art.
Keywords
Cite
@article{arxiv.1810.00974,
title = {Neural Regression Trees},
author = {Shahan Ali Memon and Wenbo Zhao and Bhiksha Raj and Rita Singh},
journal= {arXiv preprint arXiv:1810.00974},
year = {2020}
}
Comments
Accepted by The 2019 International Joint Conference on Neural Networks (IJCNN). To be published on IEEE. 8 pages, 4 figures