國立虎尾科技大學 |

Machine learning paradigms = applications of learning and analytics in intelligent systems /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning paradigms/ edited by George A. Tsihrintzis ... [et al.].
Reminder of title:	applications of learning and analytics in intelligent systems /
other author:	Tsihrintzis, George A.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xx, 548 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-15628-2
ISBN:	9783030156282

Machine learning paradigms = applications of learning and analytics in intelligent systems /
Machine learning paradigmsapplications of learning and analytics in intelligent systems /[electronic resource] :edited by George A. Tsihrintzis ... [et al.]. - Cham :Springer International Publishing :2019. - xx, 548 p. :ill., digital ;24 cm. - Learning and analytics in intelligent systems,v.12662-3447 ;. - Learning and analytics in intelligent systems ;v.1..

Chapter 1: Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems -- Chapter 2: A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failure -- Chapter 3: Differential gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research -- Chapter 4: Machine Learning Approaches for Pap-Smear Diagnosis: An Overview -- Chapter 5: Multi-Kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systems -- Chapter 6: Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitative and Qualitative Methods -- Chapter 7: Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning -- Chapter 8: Airport Data Analysis Using Common Statistical Methods and Knowledge-Based Techniques -- Chapter 9: A Taxonomy and Review of the Network Data Envelopment Analysis Literature -- Chapter 10: Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams -- Chapter 11: Analytics and Evolving Landscape of Machine Learning for Emergency Response -- Chapter 12: Social Media Analytics, Types and Methodology -- Chapter 13: Machine Learning Methods for Opinion Mining in Text: The Past and the Future -- Chapter 14: Ship Detection Using Machine Learning and Optical Imagery in the Maritime Environment -- Chapter 15: Video Analytics for Visual Surveillance and Applications: An Overview and Survey -- Chapter 16: Machine Learning in Alternate Testing of Integrated Circuits.

This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.

ISBN: 9783030156282

Standard No.: 10.1007/978-3-030-15628-2doiSubjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5 / .M334 2019

Dewey Class. No.: 006.31

Machine learning paradigms = applications of learning and analytics in intelligent systems /
LDR:03617nam a2200337 a 4500 001 941236
003 DE-He213
005 20191205100930.0
006 m d
007 cr nn 008maaau
008 200417s2019 gw s 0 eng d
020 $a 9783030156282 $q (electronic bk.)
020 $a 9783030156275 $q (paper)
024 7 $a 10.1007/978-3-030-15628-2 $2 doi
035 $a 978-3-030-15628-2
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .M334 2019
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M149 2019
245 0 0 $a Machine learning paradigms $h [electronic resource] : $b applications of learning and analytics in intelligent systems / $c edited by George A. Tsihrintzis ... [et al.].
260 $a Cham : $c 2019. $b Springer International Publishing : $b Imprint: Springer,
300 $a xx, 548 p. : $b ill., digital ; $c 24 cm.
490 1 $a Learning and analytics in intelligent systems, $x 2662-3447 ; $v v.1
505 0 $a Chapter 1: Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems -- Chapter 2: A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failure -- Chapter 3: Differential gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research -- Chapter 4: Machine Learning Approaches for Pap-Smear Diagnosis: An Overview -- Chapter 5: Multi-Kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systems -- Chapter 6: Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitative and Qualitative Methods -- Chapter 7: Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning -- Chapter 8: Airport Data Analysis Using Common Statistical Methods and Knowledge-Based Techniques -- Chapter 9: A Taxonomy and Review of the Network Data Envelopment Analysis Literature -- Chapter 10: Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams -- Chapter 11: Analytics and Evolving Landscape of Machine Learning for Emergency Response -- Chapter 12: Social Media Analytics, Types and Methodology -- Chapter 13: Machine Learning Methods for Opinion Mining in Text: The Past and the Future -- Chapter 14: Ship Detection Using Machine Learning and Optical Imagery in the Maritime Environment -- Chapter 15: Video Analytics for Visual Surveillance and Applications: An Overview and Survey -- Chapter 16: Machine Learning in Alternate Testing of Integrated Circuits.
520 $a This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.
650 0 $a Machine learning. $3 561253
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Data Engineering. $3 1226308
650 2 4 $a Machine Learning. $3 1137723
700 1 $a Tsihrintzis, George A. $3 681153
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Learning and analytics in intelligent systems ; $v v.1. $3 1228365
856 4 0 $u https://doi.org/10.1007/978-3-030-15628-2
950 $a Intelligent Technologies and Robotics (Springer-42732)