Research Advances in Machine Learning
Manzali, Youness; Gmira, Faiq; Elfar, Mohamed
ISBN 10: 6209379478 ISBN 13: 9786209379475
Published by KS Omniscriptum Publishing, 2025
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This advanced research book introduces well-designed improvements to major machine learning algorithms, including decision trees, KNN, random forests, and clustering methods. The book focuses on reducing model complexity while improving accuracy, robustness, and execution time through novel pruning, feature weighting, and ensemble strategies. The proposed approaches are experimentally validated on well-known real-world datasets, demonstrating their effectiveness and strong practical relevance.
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Bibliographic Details
Title: Research Advances in Machine Learning
Publisher: KS Omniscriptum Publishing
Publication Date: 2025
Binding: PAP
Condition: New
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RESEARCH ADVANCES IN MACHINE LEARNING
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Omniscriptum, Noor Publishing, 2025
ISBN 10: 6209379478
ISBN 13: 9786209379475
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This advanced research book introduces well-designed improvements to major machine learning algorithms, including decision trees, KNN, random forests, and clustering methods. The book focuses on reducing model complexity while improving accuracy, robustness, and execution time through novel pruning, feature weighting, and ensemble strategies. The proposed approaches are experimentally validated on well-known real-world datasets, demonstrating their effectiveness and strong practical relevance. 160 pp. Englisch. Seller Inventory # 9786209379475
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Research Advances in Machine Learning
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KS Omniscriptum Publishing, 2025
ISBN 10: 6209379478
ISBN 13: 9786209379475
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This advanced research book introduces well-designed improvements to major machine learning algorithms, including decision trees, KNN, random forests, and clustering methods. The book focuses on reducing model complexity while improving accuracy, robustness, and execution time through novel pruning, feature weighting, and ensemble strategies. The proposed approaches are experimentally validated on well-known real-world datasets, demonstrating their effectiveness and strong practical relevance. Seller Inventory # 9786209379475
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Research Advances in Machine Learning
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Research Advances in Machine Learning (Paperback)
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Paperback. Condition: new. Paperback. This advanced research book introduces well-designed improvements to major machine learning algorithms, including decision trees, KNN, random forests, and clustering methods. The book focuses on reducing model complexity while improving accuracy, robustness, and execution time through novel pruning, feature weighting, and ensemble strategies. The proposed approaches are experimentally validated on well-known real-world datasets, demonstrating their effectiveness and strong practical relevance. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786209379475
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Research Advances in Machine Learning (Paperback)
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Paperback. Condition: new. Paperback. This advanced research book introduces well-designed improvements to major machine learning algorithms, including decision trees, KNN, random forests, and clustering methods. The book focuses on reducing model complexity while improving accuracy, robustness, and execution time through novel pruning, feature weighting, and ensemble strategies. The proposed approaches are experimentally validated on well-known real-world datasets, demonstrating their effectiveness and strong practical relevance. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9786209379475
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Research Advances in Machine Learning
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Research Advances in Machine Learning
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Research Advances in Machine Learning
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