https://github.com/neurodata/df-dn-paper

Conceptual & empirical comparisons between decision forests & deep networks
https://github.com/neurodata/df-dn-paper

classification decision-trees deep-learning deep-neural-networks machine-learning random-forests

Last synced: 19 days ago
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Conceptual & empirical comparisons between decision forests & deep networks

• Host: GitHub
• URL: https://github.com/neurodata/df-dn-paper
• Owner: neurodata
• License: other
• Created: 2021-02-02T20:35:42.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2025-03-21T23:11:28.000Z (about 2 months ago)
• Last Synced: 2025-04-12T02:42:13.766Z (about 1 month ago)
• Topics: classification, decision-trees, deep-learning, deep-neural-networks, machine-learning, random-forests
• Language: Jupyter Notebook
• Homepage: https://dfdn.neurodata.io
• Size: 606 MB
• Stars: 17
• Watchers: 3
• Forks: 8
• Open Issues: 10
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

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README

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

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**DF/DN:** conceptual & empirical comparisons between **D**ecision **F**orests & **D**eep **N**etworks.

**This is preliminary work. More details will be available.**

- **Documentation:** https://dfdn.neurodata.io/

- **Abstract:** https://dfdn.neurodata.io/#abstract

- **Replication Guide:** https://dfdn.neurodata.io/#replicate

- **Benchmark Figures:** https://dfdn.neurodata.io/#benchmarks