Metaheuristics for Machine Learning New Advances and Tools /
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 ev...
Spremljeno u:
| Autor kompanije: | |
|---|---|
| Daljnji autori: | , , |
| Format: | Elektronički e-knjiga |
| Jezik: | engleski |
| Izdano: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
|
| Izdanje: | 1st ed. 2023. |
| Serija: | Computational Intelligence Methods and Applications,
|
| Teme: | |
| Online pristup: | https://doi.org/10.1007/978-981-19-3888-7 |
| Oznake: |
Dodaj oznaku
Bez oznaka, Budi prvi tko označuje ovaj zapis!
|
| Sažetak: | 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. |
|---|---|
| Opis fizičkog objekta: | 1 online resource (XV, 223 p. 1 illus.). |
| ISBN: | 9789811938887 |
| ISSN: | 2510-1773 |
| Digitalni identifikator objekta: | 10.1007/978-981-19-3888-7 |