Algorithms for Feature Selection (2nd Edition)
This Special Issue brings together cutting-edge research on algorithms, with a particular emphasis on feature selection techniques. Covering a broad range of topics—including evolutionary and ensemble methods, deep learning, high-dimensional data, time-series analysis, and textual applications—it ad...
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| Format: | Online |
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| Jezik: | engleski |
| Izdano: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| Teme: | |
| Online pristup: | ONIX_20260416T142754_9783725850655_33 |
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| _version_ | 1869529532982099968 |
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| collection | Directory of Open Access Books |
| description | This Special Issue brings together cutting-edge research on algorithms, with a particular emphasis on feature selection techniques. Covering a broad range of topics—including evolutionary and ensemble methods, deep learning, high-dimensional data, time-series analysis, and textual applications—it addresses both theoretical advancements and real-world implementations. After undergoing a rigorous peer review process, ten high-quality papers were accepted for publication within this Special Issue. The research highlights include novel models for categorical feature independence, affordable housing analysis via scenario modeling, AI-driven educational engagement strategies, video content synchronization detection, fatigue detection in drivers using multimodal sensors, and advanced feature selection techniques for bioinformatics and cancer genomics. Further contributions demonstrate applications in author identification, time-series human motion analysis, and scheduling optimization through genetic programming. This Special Issue serves as a valuable reference for researchers aiming to explore the evolving landscape of feature selection in diverse, data-intensive domains. |
| format | Online |
| id | doab-20.500.12854ir-174978 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1749782026-04-16T18:00:50Z Algorithms for Feature Selection (2nd Edition) Khan, Muhammad Adnan Algorithms and techniques for feature selection based on evolutionary search Ensemble methods for feature selection Feature selection for high dimensional data Feature selection for time series data Feature selection applications Feature selection for textual data Deep feature selection thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries This Special Issue brings together cutting-edge research on algorithms, with a particular emphasis on feature selection techniques. Covering a broad range of topics—including evolutionary and ensemble methods, deep learning, high-dimensional data, time-series analysis, and textual applications—it addresses both theoretical advancements and real-world implementations. After undergoing a rigorous peer review process, ten high-quality papers were accepted for publication within this Special Issue. The research highlights include novel models for categorical feature independence, affordable housing analysis via scenario modeling, AI-driven educational engagement strategies, video content synchronization detection, fatigue detection in drivers using multimodal sensors, and advanced feature selection techniques for bioinformatics and cancer genomics. Further contributions demonstrate applications in author identification, time-series human motion analysis, and scheduling optimization through genetic programming. This Special Issue serves as a valuable reference for researchers aiming to explore the evolving landscape of feature selection in diverse, data-intensive domains. 2026-04-16T18:00:43Z 2026-04-16T18:00:43Z 2025 book ONIX_20260416T142754_9783725850655_33 9783725850655 9783725850662 https://directory.doabooks.org/handle/20.500.12854/174978 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/11877 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-5066-2 10.3390/books978-3-7258-5066-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725850655 9783725850662 234 CH open access |
| spellingShingle | Algorithms and techniques for feature selection based on evolutionary search Ensemble methods for feature selection Feature selection for high dimensional data Feature selection for time series data Feature selection applications Feature selection for textual data Deep feature selection thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Algorithms for Feature Selection (2nd Edition) |
| title | Algorithms for Feature Selection (2nd Edition) |
| title_full | Algorithms for Feature Selection (2nd Edition) |
| title_fullStr | Algorithms for Feature Selection (2nd Edition) |
| title_full_unstemmed | Algorithms for Feature Selection (2nd Edition) |
| title_short | Algorithms for Feature Selection (2nd Edition) |
| title_sort | algorithms for feature selection 2nd edition |
| topic | Algorithms and techniques for feature selection based on evolutionary search Ensemble methods for feature selection Feature selection for high dimensional data Feature selection for time series data Feature selection applications Feature selection for textual data Deep feature selection 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 | Algorithms and techniques for feature selection based on evolutionary search Ensemble methods for feature selection Feature selection for high dimensional data Feature selection for time series data Feature selection applications Feature selection for textual data Deep feature selection 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_20260416T142754_9783725850655_33 |