Web: http://arxiv.org/abs/2201.11931

Jan. 31, 2022, 2:11 a.m. | Yan Shuo Tan, Chandan Singh, Keyan Nasseri, Abhineet Agarwal, Bin Yu

cs.LG updates on arXiv.org arxiv.org

Modern machine learning has achieved impressive prediction performance, but
often sacrifices interpretability, a critical consideration in many problems.
Here, we propose Fast Interpretable Greedy-Tree Sums (FIGS), an algorithm for
fitting concise rule-based models. Specifically, FIGS generalizes the CART
algorithm to simultaneously grow a flexible number of trees in a summation. The
total number of splits across all the trees can be restricted by a
pre-specified threshold, thereby keeping both the size and number of its trees
under control. When both …

arxiv tree

More from arxiv.org / cs.LG updates on arXiv.org

Senior Data Engineer

@ DAZN | Hammersmith, London, United Kingdom

Sr. Data Engineer, Growth

@ Netflix | Remote, United States

Data Engineer - Remote

@ Craft | Wrocław, Lower Silesian Voivodeship, Poland

Manager, Operations Data Science

@ Binance.US | Vancouver

Senior Machine Learning Researcher for Copilot

@ GitHub | Remote - Europe

Sr. Marketing Data Analyst

@ HoneyBook | San Francisco, CA