Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 34,82
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In English.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 41,81
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 37,76
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: Brand New. 9.25x7.51 inches. In Stock.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 46,15
Convertir monedaCantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
Librería: Best Price, Torrance, CA, Estados Unidos de America
EUR 33,23
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: New. SUPER FAST SHIPPING.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 36,21
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Cantidad disponible: 2 disponibles
Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Publicado por Springer Berlin Heidelberg, 2010
ISBN 10: 3642067964 ISBN 13: 9783642067969
Idioma: Inglés
Librería: Buchpark, Trebbin, Alemania
Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Publicado por Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9819920957 ISBN 13: 9789819920952
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 144,94
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 172,75
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: 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.
Librería: Best Price, Torrance, CA, Estados Unidos de America
EUR 155,68
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: New. SUPER FAST SHIPPING.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 177,61
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Publicado por Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 175,09
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMâO). EMâO algorithms, namely EMâOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations makes EMâOAs amenable to application of ML for different pursuits.Recognizing the immense potential for ML-based enhancements in the EMâO domain, this book intends to serve as an exclusive resource for both domain novices and the experienced researchers and practitioners.To achieve this goal, the book first covers the foundations of optimization, including problem and algorithm types.Then, well-structured chapters present some of the key studies on ML-based enhancements in the EMâO domain, systematically addressing important aspects. These include learning to understand the problem structure, converge better, diversify better, simultaneously converge and diversify better, and analyze the Pareto Front. In doing so, this book broadly summarizes the literature, beginning with foundational work on innovization (2003) and objective reduction (2006), and extending to the most recently proposed innovized progress operators (2021-23). It also highlights the utility of ML interventions in the search, post-optimality, and decision-making phases pertaining to the use of EMâOAs. Finally, this book shares insightful perspectives on the future potential for ML based enhancements in the EMâOA domain.To aid readers, the book includes working codes for the developed algorithms. This book will not only strengthen this emergent theme but also encourage ML researchers to develop more efficient and scalable methods that cater to the requirements of the EMâOA domain. It serves as an inspiration for further research and applications at the synergistic intersection of EMâOA and ML domains.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 185,52
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 177,60
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 172,75
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 183,21
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: ALLBOOKS1, Direk, SA, Australia
EUR 203,15
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoBrand new book. Fast ship. Please provide full street address as we are not able to ship toPOboxaddress.
Publicado por Springer Nature Singapore, Springer Nature Singapore Mai 2024, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 171,19
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. Neuware -This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMâO). EMâO algorithms, namely EMâOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations makes EMâOAs amenable to application of ML for different pursuits.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 196,09
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 196,68
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Publicado por Springer Verlag, Singapore, Singapore, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Idioma: Inglés
Librería: CitiRetail, Stevenage, Reino Unido
EUR 186,36
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: new. Hardcover. This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMaO). EMaO algorithms, namely EMaOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations makes EMaOAs amenable to application of ML for different pursuits. Recognizing the immense potential for ML-based enhancements in the EMaO domain, this book intends to serve as an exclusive resource for both domain novices and the experienced researchers and practitioners. To achieve this goal, the book first covers the foundations of optimization, including problem and algorithm types. Then, well-structured chapters present some of the key studies on ML-based enhancements in the EMaO domain, systematically addressing important aspects. These include learning to understand the problem structure, converge better, diversify better, simultaneously converge and diversify better, and analyze the Pareto Front. In doing so, this book broadly summarizes the literature, beginning with foundational work on innovization (2003) and objective reduction (2006), and extending to the most recently proposed innovized progress operators (2021-23). It also highlights the utility of ML interventions in the search, post-optimality, and decision-making phases pertaining to the use of EMaOAs. Finally, this book shares insightful perspectives on the future potential for ML based enhancements in the EMaOA domain.To aid readers, the book includes working codes for the developed algorithms. This book will not only strengthen this emergent theme but also encourage ML researchers to develop more efficient and scalable methods that cater to the requirements of the EMaOA domain. It serves as an inspiration for further research and applications at the synergistic intersection of EMaOA and ML domains. This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMaO). Finally, this book shares insightful perspectives on the future potential for ML based enhancements in the EMaOA domain.To aid readers, the book includes working codes for the developed algorithms. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 218,58
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 218,58
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 220,17
Convertir monedaCantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 2024th edition NO-PA16APR2015-KAP.
Publicado por Springer Berlin Heidelberg, 2010
ISBN 10: 3642067964 ISBN 13: 9783642067969
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 213,99
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Publicado por Springer Berlin Heidelberg, 2006
ISBN 10: 3540306765 ISBN 13: 9783540306764
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 227,74
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoGebunden. Condición: 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.
Publicado por Springer-Nature New York Inc, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 242,74
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoHardcover. Condición: Brand New. 259 pages. 9.25x6.10x9.21 inches. In Stock.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 201,18
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 201,38
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.