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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Paperback. Condición: 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. Nº de ref. del artículo: 9786209379475
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786209379475
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Paperback. Condición: 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9786209379475
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Paperback. Condición: 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. Nº de ref. del artículo: 9786209379475
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