Confident Interpretation of Bayesian Decision Tree Ensembles for Clinical Applications

By Vitaly Schetinin, Jonathan Edward Fieldsend, Derek Partridge, T. Coats, Wojtek Janusz Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández. 2007

67 citations recorded by the source corpus.

Subfields: Artificial Intelligence

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Marco F. Huber
2. Nadia Burkart
3. Paul Rad
4. Arun Das
5. Yanhong Wu
6. Dik Lun Lee
7. Xun Zhao
8. Weiwei Cui

Citations in the corpus

• iForest: Interpreting Random Forests via Visual Analytics (2019, methodology): “Surrogate models are often simple and interpretable, such as decision trees [48, 60], decision rules [16, 23], and decision sets [32].”
• Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey (2020, methodology): “Bayesian Averaging, 2007, [76] GL Other IN”
• A Survey on the Explainability of Supervised Machine Learning (2020, background): “Schetinin et al. (2007) describe the probabilistic interpretation of Bayesian decision tree ensembles.”