Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
EUR 85,49
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Seiten: 660 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 198,43
Quantità: 1 disponibili
Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 200,81
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 218,71
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Lingua: Inglese
Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2006
ISBN 10: 3540306765 ISBN 13: 9783540306764
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: BennettBooksLtd, Los Angeles, CA, U.S.A.
hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
Condizione: New. pp. 676.
EUR 248,15
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 676 Illus.
EUR 258,40
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 676.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2006
ISBN 10: 3540306765 ISBN 13: 9783540306764
Da: moluna, Greven, Germania
EUR 227,74
Quantità: Più di 20 disponibili
Aggiungi al carrelloGebunden. Condizione: New. Selected collection of recent research on multi-objective approach to machine learningRecent developments in evolutionary multi-objective optimizationApplies the concept of Pareto-optimality to machine learning Recently.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 372,63
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
Lingua: Inglese
Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2006
ISBN 10: 3540306765 ISBN 13: 9783540306764
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 416,07
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.