Nature-Inspired Computation in Data Mining and Machine Learning

Xing-Shi He

ISBN 10: 3030285553 / ISBN 13: 9783030285555

Published by Springer International Publishing, Springer International Publishing Sep 2020, 2020

About this Item

Neuware -This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 288 pp. Englisch.

Seller Inventory # 9783030285555

Bibliographic Details

• Title: Nature-Inspired Computation in Data Mining and Machine Learning
• Publisher: Springer International Publishing, Springer International Publishing Sep 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 3030285553
• ISBN 13: 9783030285555
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details.

 

Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.