Ensemble Algorithms and Their Applications
In recent decades, the development of ensemble learning methodologies has gained a significant attention from the scientific and industrial community, and found their application in various real-word problems. Theoretical and experimental evidence proved that ensemble models provide a considerably b...
保存先:
| フォーマット: | Online |
|---|---|
| 言語: | 英語 |
| 出版事項: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
|
| 主題: | |
| オンライン･アクセス: | ONIX_20210501_9783039369584_830 |
| タグ: |
タグなし, このレコードへの初めてのタグを付けませんか!
|
| _version_ | 1869518351474098176 |
|---|---|
| collection | Directory of Open Access Books |
| description | In recent decades, the development of ensemble learning methodologies has gained a significant attention from the scientific and industrial community, and found their application in various real-word problems. Theoretical and experimental evidence proved that ensemble models provide a considerably better prediction performance than single models. The main aim of this collection is to present the recent advances related to ensemble learning algorithms and investigate the impact of their application in a diversity of real-world problems. All papers possess significant elements of novelty and introduce interesting ensemble-based approaches, which provide readers with a glimpse of the state-of-the-art research in the domain. |
| format | Online |
| id | doab-20.500.12854ir-69084 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-690842024-03-30T12:51:05Z Ensemble Algorithms and Their Applications Pintelas, Panagiotis E. Livieris, Ioannis E. thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries In recent decades, the development of ensemble learning methodologies has gained a significant attention from the scientific and industrial community, and found their application in various real-word problems. Theoretical and experimental evidence proved that ensemble models provide a considerably better prediction performance than single models. The main aim of this collection is to present the recent advances related to ensemble learning algorithms and investigate the impact of their application in a diversity of real-world problems. All papers possess significant elements of novelty and introduce interesting ensemble-based approaches, which provide readers with a glimpse of the state-of-the-art research in the domain. 2021-05-01T15:40:46Z 2021-05-01T15:40:46Z 2020 book ONIX_20210501_9783039369584_830 9783039369584 9783039369591 https://directory.doabooks.org/handle/20.500.12854/69084 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/2853 https://mdpi.com/books/pdfview/book/2853 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03936-959-1 10.3390/books978-3-03936-959-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039369584 9783039369591 182 Basel, Switzerland open access |
| spellingShingle | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Ensemble Algorithms and Their Applications |
| title | Ensemble Algorithms and Their Applications |
| title_full | Ensemble Algorithms and Their Applications |
| title_fullStr | Ensemble Algorithms and Their Applications |
| title_full_unstemmed | Ensemble Algorithms and Their Applications |
| title_short | Ensemble Algorithms and Their Applications |
| title_sort | ensemble algorithms and their applications |
| topic | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20210501_9783039369584_830 |