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010 a| 2024039747;

020 a| 9798895300046q| (hardcover);

020 z| 9798895300886q| (adobe pdf);

035 a| (WaSeSS)ssj0003317353;

040 a| DLCb| engc| DLCd| WaSeSS;

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050 00 a| QA76.76.E95b| E47 2024;

082 00 a| 006.3/12| 23/eng/20241118;

130 0 a| Ensemble machine learning (Nova Science Publishers)?| UNAUTHORIZED;

245 10 a| Ensemble machine learningh| [electronic resource] :b| advances in research and applications /c| [edited by] M. A. Jabbar, Loveleen Gaur, Abdelkrim Haqiq.;

260 a| New York :b| Nova Science Publishers,c| [2024];

263 a| 2411;

300 a| pages cm.;

490 0 a| Computer science, technology and applications;

504 a| Includes bibliographical references and index.;

505 2 a| Ensemble machine learning in deep fake detection / B. N. Jyothi and M. A. Jabbar -- Ensemble machine learning in security / B. Pravallika, K. Divya, B. N. Jyothi, K. Tejaswi and M. A. Jabbar -- The ensemble method for unsupervised learning / Sankalp Joshi.;

506 a| Available only to authorized users.;

520 a| "Ensemble Machine Learning: Advances in Research and Applications" delves into the dynamic realm of ensemble methods, offering a comprehensive exploration of its evolution, methodologies, and diverse applications. Chapters are gathered from the collective wisdom of researchers, practitioners, and innovators who have pioneered this ever-evolving domain. This book serves as a compendium, bringing together theoretical foundations, cutting-edge advancements, and practical insights, catering to both seasoned experts and those venturing into the intricate world of ensemble learning. Each chapter encapsulates the essence of collaboration among diverse models, unveiling the intricacies of ensemble techniques, their fusion strategies, and their impact across industries. This book serves as a guiding beacon for enthusiasts, researchers, and practitioners navigating the intricate landscape of ensemble machine learning, fostering innovation, and paving the way for future breakthroughs"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 0 a| Ensemble learning (Machine learning)=| ^A1486579;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Jabbar, M. A.q| (Meerja Akhil)?| UNAUTHORIZED;

700 1 a| Gaur, Loveleen.=| ^A1434510;

700 1 a| Haqiq, Abdelkrim.?| UNAUTHORIZED;

856 40 z| Full text available from Ebook Central - Academic Completeu| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=31619116;

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Ensemble machine learning advances in research and applications / [edited by] M. A. Jabbar, Loveleen Gaur, Abdelkrim Haqiq.

Other author	Jabbar, M. A. (Meerja Akhil)
Other author	Gaur, Loveleen.
Other author	Haqiq, Abdelkrim.
Format	Electronic
Publication Info	New York : Nova Science Publishers, [2024]
Description	pages cm.
Supplemental Content	Full text available from Ebook Central - Academic Complete
Subjects	Ensemble learning (Machine learning)

Uniform title	Ensemble machine learning (Nova Science Publishers)
Series	Computer science, technology and applications
Partial contents	Ensemble machine learning in deep fake detection / B. N. Jyothi and M. A. Jabbar -- Ensemble machine learning in security / B. Pravallika, K. Divya, B. N. Jyothi, K. Tejaswi and M. A. Jabbar -- The ensemble method for unsupervised learning / Sankalp Joshi.
Abstract	"Ensemble Machine Learning: Advances in Research and Applications" delves into the dynamic realm of ensemble methods, offering a comprehensive exploration of its evolution, methodologies, and diverse applications. Chapters are gathered from the collective wisdom of researchers, practitioners, and innovators who have pioneered this ever-evolving domain. This book serves as a compendium, bringing together theoretical foundations, cutting-edge advancements, and practical insights, catering to both seasoned experts and those venturing into the intricate world of ensemble learning. Each chapter encapsulates the essence of collaboration among diverse models, unveiling the intricacies of ensemble techniques, their fusion strategies, and their impact across industries. This book serves as a guiding beacon for enthusiasts, researchers, and practitioners navigating the intricate landscape of ensemble machine learning, fostering innovation, and paving the way for future breakthroughs"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2024039747
ISBN	9798895300046 (hardcover)
ISBN	(adobe pdf)

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Ensemble machine learning advances in research and applications / [edited by] M. A. Jabbar, Loveleen Gaur, Abdelkrim Haqiq.

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