Classification by ordinal sums of conjunctive and disjunctive functions for explainable AI and interpretable machine learning solutions
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Classification by ordinal sums of conjunctive and disjunctive functions for explainable AI and interpretable machine learning solutions
Authors
Keywords
Explainable AI, Interpretable Machine Learning (ML), Interactive ML, Aggregation functions, Ordinal sums, Glass-box, Transparency
Journal
KNOWLEDGE-BASED SYSTEMS
Volume 220, Issue -, Pages 106916
Publisher
Elsevier BV
Online
2021-03-03
DOI
10.1016/j.knosys.2021.106916
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI
- (2021) Andreas Holzinger et al. Information Fusion
- Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?
- (2019) Alberto Fernandez et al. IEEE Computational Intelligence Magazine
- Causability and explainabilty of artificial intelligence in medicine
- (2019) Andreas Holzinger et al. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
- Concise Fuzzy System Modeling Integrating Soft Subspace Clustering and Sparse Learning
- (2019) Peng Xu et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Fuzzy functional dependencies and linguistic interpretations employed in knowledge discovery tasks from relational databases
- (2019) Miljan Vučetić et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- The axiomatization of asymmetric disjunction and conjunction
- (2019) Miroslav Hudec et al. Information Fusion
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
- (2019) Alejandro Barredo Arrieta et al. Information Fusion
- Methods for interpreting and understanding deep neural networks
- (2018) Grégoire Montavon et al. DIGITAL SIGNAL PROCESSING
- Multi-View Fuzzy Logic System with the Cooperation between Visible and Hidden Views
- (2018) Te Zhang et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Interactive machine learning: experimental evidence for the human in the algorithmic loop
- (2018) Andreas Holzinger et al. APPLIED INTELLIGENCE
- Data-Driven Elastic Fuzzy Logic System Modeling: Constructing a Concise System with Human-like Inference Mechanism
- (2017) Jiangbin Zhang et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Dermatologist-level classification of skin cancer with deep neural networks
- (2017) Andre Esteva et al. NATURE
- Classification of breast cancer histology images using Convolutional Neural Networks
- (2017) Teresa Araújo et al. PLoS One
- Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model
- (2015) Zhaohong Deng et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints
- (2015) Tjeerd van der Ploeg et al. BMC Medical Research Methodology
- Integration of data selection and classification by fuzzy logic
- (2012) Miroslav Hudec et al. EXPERT SYSTEMS WITH APPLICATIONS
- Interpretability constraints for fuzzy information granulation
- (2008) C. Mencar et al. INFORMATION SCIENCES
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now