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Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science) - Tapa blanda
Sinopsis
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics.
"Automatic Design of Decision-Tree Induction Algorithms" would be highly useful for machine learning and evolutionary computation students and researchers alike.
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Reseña del editor
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics.
"Automatic Design of Decision-Tree Induction Algorithms" would be highly useful for machine learning and evolutionary computation students and researchers alike.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Automatic Design of Decision-Tree Induction Algorithms
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Springer International Publishing Mrz 2015, 2015
ISBN 10: 3319142305
ISBN 13: 9783319142302
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics.'Automatic Design of Decision-Tree Induction Algorithms' would be highly useful for machine learning and evolutionary computation students and researchers alike. 188 pp. Englisch. Nº de ref. del artículo: 9783319142302
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Automatic Design of Decision-Tree Induction Algorithms
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Springer International Publishing, Springer International Publishing, 2015
ISBN 10: 3319142305
ISBN 13: 9783319142302
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics.'Automatic Design of Decision-Tree Induction Algorithms' would be highly useful for machine learning and evolutionary computation students and researchers alike. Nº de ref. del artículo: 9783319142302
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Automatic Design of Decision-Tree Induction Algorithms
Publicado por
Springer International Publishing, 2015
ISBN 10: 3319142305
ISBN 13: 9783319142302
Nuevo
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Automatic Design of Decision-tree Induction Algorithms
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Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)
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Automatic Design of Decision-Tree Induction Algorithms
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Automatic Design of Decision-tree Induction Algorithms
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