HackerPapers

arXiv:2210.05189cs.LG

Neural Networks are Decision Trees

Caglar Aytekin

Abstract

In this manuscript, we show that any neural network with any activation function can be represented as a decision tree. The representation is equivalence and not an approximation, thus keeping the accuracy of the neural network exactly as is. We believe that this work provides better understanding of neural networks and paves the way to tackle their black-box nature. We share equivalent trees of some neural networks and show that besides providing interpretability, tree representation can also achieve some computational advantages for small networks. The analysis holds both for fully connected and convolutional networks, which may or may not also include skip connections and/or normalizations.

arXiv comments
Journal reference
DOI
Subjects
cs.LGMachine Learning

On Hacker News

Linked by 3 identifiable commenters in 3 comments across 3 threads, from Feb 2023 to Mar 2026. Found in 4 HN submissions from Oct 2022 to Oct 2022. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments3 threads

  1. Decision trees – the unreasonable power of nested decision rules 1 comment

    • > single bit neural networks are decision trees. I didn't exactly understood what was meant here, so I went out and read a little. There is an interesting paper called "Neural Networks are Decision Trees" [1]. Thing is, this does not imply a nice mapping of neural networks onto…

      smokelView on HNParent context

  2. 20x Faster Background Removal in the Browser Using ONNX Runtime with WebGPU 1 comment

    • There is some work to convert NNs to decision trees. https://towardsdatascience.com/neural-networks-as-decision-t... https://arxiv.org/abs/2210.05189 I haven't reviewed any of it, I only know of it tangentially. https://www.semanticscholar.org/paper/Converting-A-Trained-N...…

      sitkackView on HNParent context

  3. Ask HN: Is anyone else getting AI fatigue? 1 comment

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.