An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models-Reference-Cited by-同舟云学术

An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models

Published:2011-04 Issue:1 Volume:51 Page:141-154
ISSN:0167-9236
Container-title:Decision Support Systems
language:en
Short-container-title:Decision Support Systems

Author:

Huysmans Johan,Dejaeger Karel,Mues Christophe,Vanthienen Jan,Baesens Bart

Publisher

Elsevier BV

Subject

Information Systems and Management,Arts and Humanities (miscellaneous),Developmental and Educational Psychology,Information Systems,Management Information Systems

Reference63 articles.

1. Survey and critique of techniques for extracting rules from trained artificial neural networks;Andrews;Knowledge Based Systems,1995

2. Benchmarking state of the art classification algorithms for credit scoring;Baesens;Journal of the Operational Research Society,2003

3. Behavioral aspects of information processing for the design of management information systems;Benbasat;IEEE Transactions on Systems, Man, and Cybernetics,1982

4. An experimental program investigating color-enhanced and graphical information presentation: An integration of the findings;Benbasat;Communications of the ACM,1986

5. Classification and Regression Trees;Breiman,1984

Cited by 250 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An attribution graph-based interpretable method for CNNs;Neural Networks;2024-11

2. Reducing the incidence of biased algorithmic decisions through feature importance transparency: an empirical study;European Journal of Information Systems;2024-09-02

3. Leveraging explainable AI for informed building retrofit decisions: Insights from a survey;Energy and Buildings;2024-09

4. An interpretable machine learning methodology to generate interaction effect hypotheses from complex datasets;Decision Sciences;2024-08-13

5. HEX: Human-in-the-loop explainability via deep reinforcement learning;Decision Support Systems;2024-08