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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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9786209379475
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Paperback. Zustand: 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. Bestandsnummer des Verkäufers 9786209379475
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9786209379475
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Taschenbuch. Zustand: Neu. RESEARCH ADVANCES IN MACHINE LEARNING | Youness Manzali (u. a.) | Taschenbuch | Englisch | 2025 | KS OmniScriptum Publishing | EAN 9786209379475 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 134433970
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