國立高雄大學圖資館 |

Language: English

Back

Nature-inspired computation in data ...

He, Xing-Shi.

Nature-inspired computation in data mining and machine learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nature-inspired computation in data mining and machine learningedited by Xin-She Yang, Xing-Shi He.
other author:	Yang, Xin-She.
Published:	Cham :Springer International Publishing :2020.
Description:	xi, 273 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Natural computation.
Online resource:	https://doi.org/10.1007/978-3-030-28553-1
ISBN:	9783030285531$q(electronic bk.)

Nature-inspired computation in data mining and machine learning
Nature-inspired computation in data mining and machine learning[electronic resource] /edited by Xin-She Yang, Xing-Shi He. - Cham :Springer International Publishing :2020. - xi, 273 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8551860-949X ;. - Studies in computational intelligence ;v. 216..

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.

ISBN: 9783030285531$q(electronic bk.)

Standard No.: 10.1007/978-3-030-28553-1doiSubjects--Topical Terms:

339160
Natural computation.

LC Class. No.: QA76.9.N37 / N37 2020

Dewey Class. No.: 006.38

Nature-inspired computation in data mining and machine learning
LDR:02350nmm a2200325 a 4500 001 593220
003 DE-He213
005 20200706040907.0
006 m d
007 cr nn 008maaau
008 210727s2020 sz s 0 eng d
020 $a 9783030285531$q(electronic bk.)
020 $a 9783030285524$q(paper)
024 7 $a 10.1007/978-3-030-28553-1 $2 doi
035 $a 978-3-030-28553-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N37 $b N37 2020
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.38 $2 23
090 $a QA76.9.N37 $b N285 2020
245 0 0 $a Nature-inspired computation in data mining and machine learning $h [electronic resource] / $c edited by Xin-She Yang, Xing-Shi He.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xi, 273 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.855
520 $a 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.
650 0 $a Natural computation. $3 339160
650 0 $a Data mining. $3 184440
650 0 $a Machine learning. $3 188639
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
700 1 $a Yang, Xin-She. $3 522569
700 1 $a He, Xing-Shi. $3 841930
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 216. $3 380871
856 4 0 $u https://doi.org/10.1007/978-3-030-28553-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)