Cargando…
Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation
Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct opera...
Autores principales: | Burkhardt, Sophie, Brugger, Jannis, Wagner, Nicolas, Ahmadi, Zahra, Kersting, Kristian, Kramer, Stefan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336635/ https://www.ncbi.nlm.nih.gov/pubmed/34368757 http://dx.doi.org/10.3389/frai.2021.642263 |
Ejemplares similares
-
AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
por: Blüml, Jannis, et al.
Publicado: (2023) -
An Empirical Investigation Into Deep and Shallow Rule Learning
por: Beck, Florian, et al.
Publicado: (2021) -
Improving rule-based classification using Harmony Search
por: Hasanpour, Hesam, et al.
Publicado: (2019) -
Aspect extraction on user textual reviews using multi-channel convolutional neural network
por: Da’u, Aminu, et al.
Publicado: (2019) -
Machine learning of symbolic compositional rules with genetic programming: dissonance treatment in Palestrina
por: Anders, Torsten, et al.
Publicado: (2019)