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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: 2 months 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 (almost 4 years ago)
Default Branch: main
Last Pushed: 2024-04-05T13:52:48.000Z (10 months ago)
Last Synced: 2024-04-05T14:54:10.360Z (10 months ago)
Topics: classification, decision-trees, deep-learning, deep-neural-networks, machine-learning, random-forests
Language: Jupyter Notebook
Homepage: https://dfdn.neurodata.io
Size: 111 MB
Stars: 16
Watchers: 4
Forks: 8
Open Issues: 11
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?

[![arXiv](https://img.shields.io/badge/arXiv-2108.13637-red.svg?style=flat)](https://arxiv.org/abs/2108.13637)

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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