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Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings de Andreas Holzinger

Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings: Lecture Notes in Computer Science, cartea 11713

Editat de Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl
en Limba Engleză Paperback – 23 aug 2019
This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.
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Specificații

ISBN-13: 9783030297251
ISBN-10: 303029725X
Pagini: 350
Ilustrații: XIII, 416 p. 138 illus., 98 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.6 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI

Locul publicării:Cham, Switzerland

Cuprins

KANDINSKY Patterns as IQ-Test for machine learning.- Machine Learning Explainability Through Comprehensible Decision Trees.- New Frontiers in Explainable AI: Understanding the GI to Interpret the GO.- Automated Machine Learning for Studying the Trade-off Between Predictive Accuracy and Interpretability.- Estimating the Driver Status Using Long Short Term Memory.- Using Relational Concept Networks for Explainable Decision Support.- Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking.- Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Deep Learning and Image Augmentation.- Semi-automated Quality Assurance for Domain-expert-driven Data Exploration - An Application to Principal Component Analysis.- Ranked MSD: A New Feature Ranking and Feature Selection Approach for Biomarker Identification.- How to improve the adaptation phase of the CBR in the medical domain.- Machine Learning for Family Doctors: A Case of Cluster Analysis for studying Aging Associated Comorbidities and Frailty.- Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement.- An Evaluation on Robustness and Utility of Fingerprinting Schemes.- Differentially Private Obfuscation of Facial Images.- Insights into Learning Competence through Probabilistic Graphical Models.- Sparse Nerves in Practice.- Backdoor Attacks in Neural Networks - a Systematic Evaluation on Multiple Traffic Sign Datasets.- Deep Learning for Proteomics Data for Feature Selection and Classification.- Package and Classify Wireless Product Features to Their Sales Items and Categories Automatically.- Temporal diagnosis of discrete-event systems with dual knowledge Compilation.- A Case for Guided Machine Learning.- Using Ontologies to Express Prior Knowledge for Genetic Programming.- Real Time Hand Movement Trajectory Tracking for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language.- Commonsense Reasoning using Theorem Proving and Machine Learning.- Deep structured semantic model for recommendations with heterogeneous side information in e-commerce.

Caracteristici

Includes supplementary material: sn.pub/extras