Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems

Author:   George A. Tsihrintzis ,  Maria Virvou ,  Evangelos Sakkopoulos ,  Lakhmi C. Jain
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   1
ISBN:  

9783030156275


Pages:   548
Publication Date:   15 July 2019
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems


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Overview

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.

Full Product Details

Author:   George A. Tsihrintzis ,  Maria Virvou ,  Evangelos Sakkopoulos ,  Lakhmi C. Jain
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   1
Weight:   1.010kg
ISBN:  

9783030156275


ISBN 10:   3030156273
Pages:   548
Publication Date:   15 July 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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

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