Machine Learning and Knowledge Extraction 1st Edition by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl ISBN 9783031144622 3031144627

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Product details:

ISBN 10: 3031144627
ISBN 13: 9783031144622
Author: Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl

Machine Learning and Knowledge Extraction 1st Edition Table of contents:

1. Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions
2. The Explanation Game: Explaining Machine Learning Models Using Shapley Values
3. Back to the Feature: A Neural-Symbolic Perspective on Explainable AI
4. Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification
5. Explainable Reinforcement Learning: A Survey
6. A Projected Stochastic Gradient Algorithm for Estimating Shapley Value Applied in Attribute Importance
7. Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees
8. Explainable Deep Learning for Fault Prognostics in Complex Systems: A Particle Accelerator Use-Case
9. eXDiL: A Tool for Classifying and eXplaining Hospital Discharge Letters
10. Cooperation Between Data Analysts and Medical Experts: A Case Study
11. A Study on the Fusion of Pixels and Patient Metadata in CNN-Based Classification of Skin Lesion Images
12. The European Legal Framework for Medical AI
13. An Efficient Method for Mining Informative Association Rules in Knowledge Extraction
14. Interpretation of SVM Using Data Mining Technique to Extract Syllogistic Rules
15. Non-local Second-Order Attention Network for Single Image Super Resolution
16. ML-ModelExplorer: An Explorative Model-Agnostic Approach to Evaluate and Compare Multi-class Classifiers
17. Subverting Network Intrusion Detection: Crafting Adversarial Examples Accounting for Domain-Specific Constraints
18. Scenario-Based Requirements Elicitation for User-Centric Explainable AI
19. On-the-fly Black-Box Probably Approximately Correct Checking of Recurrent Neural Networks
20. Active Learning for Auditory Hierarchy
21. Improving Short Text Classification Through Global Augmentation Methods
22. Interpretable Topic Extraction and Word Embedding Learning Using Row-Stochastic DEDICOM
23. A Clustering Backed Deep Learning Approach for Document Layout Analysis
24. Calibrating Human-AI Collaboration: Impact of Risk, Ambiguity and Transparency on Algorithmic Bias
25. Applying AI in Practice: Key Challenges and Lessons Learned
26. Function Space Pooling for Graph Convolutional Networks
27. Analysis of Optical Brain Signals Using Connectivity Graph Networks
28. Property-Based Testing for Parameter Learning of Probabilistic Graphical Models
29. An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge
30. Inter-space Machine Learning in Smart Environments

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Tags: Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl, Machine Learning, Knowledge Extraction