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Machine Learning and Knowledge Extraction

Overview of attention for book
Machine Learning and Knowledge Extraction
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI
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    Chapter 2 Approximation of SHAP Values for Randomized Tree Ensembles
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    Chapter 3 Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning
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    Chapter 4 Effects of Fairness and Explanation on Trust in Ethical AI
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    Chapter 5 Towards Refined Classifications Driven by SHAP Explanations
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    Chapter 6 Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models’ Calibration
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    Chapter 7 The ROC Diagonal is Not Layperson’s Chance: A New Baseline Shows the Useful Area
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    Chapter 8 Debiasing MDI Feature Importance and SHAP Values in Tree Ensembles
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    Chapter 9 The Influence of User Diversity on Motives and Barriers when Using Health Apps - A Conjoint Investigation of the Intention-Behavior Gap
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    Chapter 10 Identifying Fraud Rings Using Domain Aware Weighted Community Detection
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    Chapter 11 Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation
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    Chapter 12 Semantic Causal Abstraction for Event Prediction
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    Chapter 13 An Evaluation Study of Intrinsic Motivation Techniques Applied to Reinforcement Learning over Hard Exploration Environments
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    Chapter 14 Towards Generating Financial Reports from Tabular Data Using Transformers
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    Chapter 15 Evaluating the Performance of SOBEK Text Mining Keyword Extraction Algorithm
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    Chapter 16 Classification of Screenshot Image Captured in Online Meeting System
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    Chapter 17 A Survey on the Application of Virtual Reality in Event-Related Potential Research
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    Chapter 18 Visualizing Large Collections of URLs Using the Hilbert Curve
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    Chapter 19 How to Reduce the Time Necessary for Evaluation of Tree-Based Models
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    Chapter 20 An Empirical Analysis of Synthetic-Data-Based Anomaly Detection
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    Chapter 21 SECI Model in Data-Based Procedure for the Assessment of the Frailty State in Diabetic Patients
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    Chapter 22 Comparing Machine Learning Correlations to Domain Experts’ Causal Knowledge: Employee Turnover Use Case
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    Chapter 23 Machine Learning and Knowledge Extraction to Support Work Safety for Smart Forest Operations
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Title
Machine Learning and Knowledge Extraction
Published by
Springer International Publishing, August 2022
DOI 10.1007/978-3-031-14463-9
ISBNs
978-3-03-114462-2, 978-3-03-114463-9
Editors

Holzinger, Andreas, Kieseberg, Peter, Tjoa, A Min, Weippl, Edgar

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