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Metaheuristics for Machine Learning : New Advances and Tools / edited by Mansour Eddaly, Bassem Jarboui, Patrick Siarry
(Computational Intelligence Methods and Applications. ISSN:25101773)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	XV, 223 p. 1 illus : online resource
著者標目	Eddaly, Mansour editor Jarboui, Bassem editor Siarry, Patrick editor SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002408	Computer Scinece R0 2005-6,2022-3				9789811938887

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一般注記	1. From metaheuristics to automatic programming -- 2. Biclustering Algorithms Based on Metaheuristics: A Review -- 3. A Metaheuristic Perspective on Learning Classifier Systems -- 4. An evolutionary clustering approach using metaheuristics and unsupervised machine learning algorithms for customer segmentation -- 5. Applications of Metaheuristics in Parameter Optimization in Manufacturing Processes and Machine Health Monitoring -- 6. Evolving Machine Learning-based classifiers by metaheuristic approaches for underwater sonar target detection and recognition -- 7. Solving the Quadratic Knapsack Problem using a GRASP algorithm based on a multi-swap local search -- 8. Algorithmic vs Processing Manipulations to Scale Genetic Programming to Big Data Mining -- 9. Dynamic assignment problem of parking slots Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking HTTP:URL=https://doi.org/10.1007/978-981-19-3888-7
件　名	LCSH:Machine learning LCSH:Artificial intelligence LCSH:Computer science FREE:Machine Learning FREE:Artificial Intelligence FREE:Theory and Algorithms for Application Domains
分　類	LCC:Q325.5-.7 DC23:006.31
書誌ID	EB00001796
ISBN	9789811938887