Decision Forests

All content related to Decision Forests on my website. Original research/software have an emoji next to it. A full list of topics is also available.

1. 🔬 treeple

   Extends scikit-learn decision trees to do oblique splits, manifold learning, hypothesis testing, etc. I am a core contributor and maintainer of this project.

2. 📝 Simplest Streaming Trees

   Haoyin Xu, Jayanta Dey, Sambit Panda, Joshua T. Vogelstein
   arXiv, 2023

   Developed a streaming algorithm for decision trees based on the simplest possible extension of them.

3. 📝 Learning Interpretable Characteristic Kernels via Decision Forests

   Sambit Panda*, Cencheng Shen*, Joshua T. Vogelstein
   arXiv, 2023

   Demonstrates the kernel derived from random forest is characteristic and develops a hypothesis test based on that fact (KMERF).

4. 📝 When are Deep Networks really better than Decision Forests at small sample sizes, and how?

   Haoyin Xu, Kaleab A. Kinfu, Will LeVine, Sambit Panda, Jayanta Dey, Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, Florian Engert, Christopher M. White, Joshua T. Vogelstein, Carey E. Priebe
   arXiv, 2021

   Illustrates that forest based methods excel at tabular data classification at small sample sizes while networks excel at larger sample sizes.