- Home
- Publications
- Publication Search
- Publication Details
Title
A Survey of Methods for Explaining Black Box Models
Authors
Keywords
-
Journal
ACM COMPUTING SURVEYS
Volume 51, Issue 5, Pages 1-42
Publisher
Association for Computing Machinery (ACM)
Online
2018-08-22
DOI
10.1145/3236009
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Regulating Autonomous Systems: Beyond Standards
- (2017) David Danks et al. IEEE INTELLIGENT SYSTEMS
- Prediction and explanation in social systems
- (2017) Jake M. Hofman et al. SCIENCE
- Evaluating the Visualization of What a Deep Neural Network Has Learned
- (2017) Wojciech Samek et al. IEEE Transactions on Neural Networks and Learning Systems
- Learning From Explanations Using Sentiment and Advice in RL
- (2017) Samantha Krening et al. IEEE Transactions on Cognitive and Developmental Systems
- Visualizing Deep Convolutional Neural Networks Using Natural Pre-images
- (2016) Aravindh Mahendran et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
- (2015) Benjamin Letham et al. Annals of Applied Statistics
- Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
- (2015) Alex Goldstein et al. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
- The Computerized Adaptive Diagnostic Test for Major Depressive Disorder (CAD-MDD)
- (2013) Robert D. Gibbons et al. JOURNAL OF CLINICAL PSYCHIATRY
- A multidisciplinary survey on discrimination analysis
- (2013) Andrea Romei et al. KNOWLEDGE ENGINEERING REVIEW
- On the interpretation of weight vectors of linear models in multivariate neuroimaging
- (2013) Stefan Haufe et al. NEUROIMAGE
- Using sensitivity analysis and visualization techniques to open black box data mining models
- (2012) Paulo Cortez et al. INFORMATION SCIENCES
- Prototype selection for interpretable classification
- (2011) Jacob Bien et al. Annals of Applied Statistics
- Performance of classification models from a user perspective
- (2011) David Martens et al. DECISION SUPPORT SYSTEMS
- Reverse Engineering the Neural Networks for Rule Extraction in Classification Problems
- (2011) M. Gethsiyal Augasta et al. NEURAL PROCESSING LETTERS
- An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models
- (2010) Johan Huysmans et al. DECISION SUPPORT SYSTEMS
- Building comprehensible customer churn prediction models with advanced rule induction techniques
- (2010) Wouter Verbeke et al. EXPERT SYSTEMS WITH APPLICATIONS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search