arXiv Open Access 2021

Interpretable Decision Trees Through MaxSAT

Josep Alos Carlos Ansotegui Eduard Torres

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Abstrak

We present an approach to improve the accuracy-interpretability trade-off of Machine Learning (ML) Decision Trees (DTs). In particular, we apply Maximum Satisfiability technology to compute Minimum Pure DTs (MPDTs). We improve the runtime of previous approaches and, show that these MPDTs can outperform the accuracy of DTs generated with the ML framework sklearn.

Topik & Kata Kunci

cs.AI cs.LG

Penulis (3)

Josep Alos

Carlos Ansotegui

Eduard Torres

Format Sitasi

APA MLA BibTeX

Alos, J., Ansotegui, C., Torres, E. (2021). Interpretable Decision Trees Through MaxSAT. https://arxiv.org/abs/2110.13854

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓