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Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
| Date | Stars |
|---|---|
| 2026-07-31 | 532 |
| 2026-08-01 | 532 |
| 2026-08-06 | 531 |
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# Neural Oblivious Decision Ensembles A supplementary code for [Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data](https://arxiv.org/abs/1909.06312) paper. <img src="./images/densetree.png" width=600px> # What does it do? It learns deep ensembles of oblivious differentiable decision trees on tabular data # What do i need to run it? * A machine with some CPU (preferably 2+ free cores) and GPU(s) * Running without GPU is possible but takes 8-10x as long even on high-end CPUs * Our implementation is memory inefficient and may require a lot of GPU memory to converge * Some popular Linux x64 distribution * Tested on Ubuntu16.04, should work fine on any popular linux64 and even MacOS; * Windows and x32 systems may require heavy wizardry to run; * When in doubt, use Docker, preferably GPU-enabled (i.e. nvidia-docker) # How do I run it? 1. Clone or download this repo. `cd` yourself to it's root directory. 2. Grab or build a working python enviromnent. [Anaconda](https://www.anaconda.com/) works fine. 3. Install packages from `requirements.txt` * It is critical that you use __torch >= 1.1__, not 1.0 or earlier * You will also need jupyter or some other way to work with .ipynb files 4. Run jupyter notebook and open a notebook in `./notebooks/` * Before you run the first cell, change `%env CUDA_VISIBLE_DEVICES=#` to an index that you plan to use. * The notebook downloads data from dropbox. You will need __1-5Gb__ of disk space depending on dataset. We showcase two typical learning scenarios for classification and regression. Please consult the original paper for training details.
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matched fp:188d9a48007427df, llm:Repository description: 'Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data' (topic: tabular DL, implementation likely of NODEnet/NODEE)
matched fp:188d9a48007427df, llm:Repository description: 'Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data' (topic: tabular DL, implementation likely of NODEnet/NODEE)
matched fp:188d9a48007427df, llm:Repository description: 'Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data' (topic: tabular DL, implementation likely of NODEnet/NODEE)