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Machine learning and knowledge extra...

International Cross-Domain Conference for Machine Learning and Knowledge Extraction (2019 :)

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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 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning and knowledge extraction/ edited by Andreas Holzinger ... [et al.].
Reminder of title:	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 /
remainder title:	CD-MAKE 2019
other author:	Holzinger, Andreas.
corporate name:	International Cross-Domain Conference for Machine Learning and Knowledge Extraction
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xiii, 416 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Machine learning - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-29726-8
ISBN:	9783030297268

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 /
Machine learning and knowledge extractionthird 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 /[electronic resource] :CD-MAKE 2019edited by Andreas Holzinger ... [et al.]. - Cham :Springer International Publishing :2019. - xiii, 416 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,117130302-9743 ;. - Lecture notes in computer science ;11713..

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.

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.

ISBN: 9783030297268

Standard No.: 10.1007/978-3-030-29726-8doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5 / .I58 2019

Dewey Class. No.: 006.31

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 /
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