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Record Nr. |
UNINA9910743352903321 |
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Titolo |
Advances in machine learning for big data analysis / / Satchidananda Dehuri, Yen-Wei Chen, editors |
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Pubbl/distr/stampa |
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Singapore : , : Springer, , [2022] |
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©2022 |
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ISBN |
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981-16-8929-6 |
981-16-8930-X |
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Descrizione fisica |
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1 online resource (xix, 239 pages) : illustrations (some color), charts |
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Collana |
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Intelligent Systems Reference Library ; ; v.218 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Machine learning |
Artificial intelligence - Data processing |
Big data |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1. Multi-objective ant colony optimization : an updated review of approaches and applications -- 2. Cost-effective detection of cyber physical system attacks -- 3. A prognostic approach to crime analysis -- 4. A counter-based profiling scheme for improving locality through data and reducer placement -- 5. Hybridization of the higher order neural networks with the evolutionary optimization algorithms--an application to financial time series forecasting -- 6. Supply chain management (SCM) : employing various big data and metaheuristic strategies -- 7. Value of random vector functional link neural networks in software development effort estimation -- 8. Hybrid approach to prevent accidents at railway : an assimilation of big data, IoT and cloud -- 9. Hybrid decision tree for machine learning : a big data perspective. |
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Sommario/riassunto |
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This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. |
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