Machine Learning and Knowledge Extraction : 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, Vienna, Austria, August 23–26, 2022, Proceedings / edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl.

Format:

Book

Contributor:

Holzinger, Andreas, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13480

Language:

English

Subjects (All):

Artificial intelligence.

Software engineering.

Database management.

Data mining.

Information storage and retrieval systems.

Machine theory.

Artificial Intelligence.

Software Engineering.

Database Management.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Formal Languages and Automata Theory.

Local Subjects:

Artificial Intelligence.

Software Engineering.

Database Management.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Formal Languages and Automata Theory.

Physical Description:

1 online resource (390 pages)

Edition:

1st ed. 2022.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

Summary:

This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022. The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Contents:

Explain to Not Forget: Defending Catastrophic Forgetting with XAI

Approximation of SHAP values for Randomized Tree Ensembles

Color shadows (part I): exploratory usability evaluation of activation maps in radiological machine learning

Effects of Fairness and Explanation on Trust in Ethical AI

Towards Refined Classifications driven by SHAP explanations

Global Intepretable Calibration Index, a New Metric to Estimate Machine Learning Models' Calibration

The ROC Diagonal is not Layperson’s Chance: a New Baseline Shows the Useful Area

Debiasing MDI Feature Importance and SHAP values in Tree Ensembles

The Influence of User Diversity on Motives and Barriers when Using Health Apps - A Conjoint Investigation of the Intention-Behavior Gap

Identifying Fraud Rings Using Domain Aware Weighted Community Detection

Capabilities, limitations and challenges of style transfer with CycleGANs: a study on automatic ring design generation

Semantic Causal Abstraction for Event Prediction

An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments

Towards Generating Financial Reports From Tabular Data Using Transformers

Evaluating the performance of SOBEK text mining keyword extraction algorithm

Classification of Screenshot Image Captured in Online Meeting System

A survey on the application of virtual reality in event-related potential research

Visualizing Large Collections of URLs Using the Hilbert Curve

How to Reduce the Time Necessary for Evaluation of Tree-based Models

An Empirical Analysis of and Guidelines for Synthetic-Data-based Anomaly Detection

SECI Model in Data-Based Procedure for the Assessment of the Frailty State in Diabetic Patients

Comparing machine learning correlations to domain experts’ causal knowledge: Employee turnover use case

Machine learning and knowledge extraction to support work safety for smart forest operations.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Holzinger, Andreas Machine Learning and Knowledge Extraction

ISBN:

3-031-14463-5