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Natureinspired Computation In Data Mining And Machine Learning 1st Ed 2020 Xinshe Yang

  • SKU: BELL-10799632
Natureinspired Computation In Data Mining And Machine Learning 1st Ed 2020 Xinshe Yang
$ 31.00 $ 45.00 (-31%)

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Natureinspired Computation In Data Mining And Machine Learning 1st Ed 2020 Xinshe Yang instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 8.11 MB
Author: Xin-She Yang, Xing-Shi He
ISBN: 9783030285524, 9783030285531, 3030285529, 3030285537
Language: English
Year: 2020
Edition: 1st ed. 2020

Product desciption

Natureinspired Computation In Data Mining And Machine Learning 1st Ed 2020 Xinshe Yang by Xin-she Yang, Xing-shi He 9783030285524, 9783030285531, 3030285529, 3030285537 instant download after payment.

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.

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