Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)

Barros, Rodrigo C. C.; De Carvalho, Andr� C.P.L.F; Freitas, Alex A.

ISBN 10: 3319142305 ISBN 13: 9783319142302

Edit� par Springer, 2015

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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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Titre : Automatic Design of Decision-Tree Induction ...
�diteur : Springer
Date d'�dition : 2015
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Barros:Automatic Design of Decision-Tre (eng)

Barros, Rodrigo C.

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Automatic Design of Decision-Tree Induction Algorithms

Rodrigo C. Barros|Andr� C.P.L.F de Carvalho|Alex A. Freitas

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ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Automatic Design of Decision-Tree Induction Algorithms

Rodrigo C. Barros (u. a.)

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Automatic Design of Decision-tree Induction Algorithms

Barros, Rodrigo C.; De Carvalho, Andr� C. P. L. F.; Freitas, Alex

Edit� par Springer, 2015

ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)

Barros, Rodrigo C. C.; De Carvalho, Andr� C.P.L.F; Freitas, Alex A.

Edit� par Springer, 2015

ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Automatic Design of Decision-Tree Induction Algorithms

Rodrigo C. Barros

Edit� par Springer International Publishing, Springer International Publishing M�r 2015, 2015

ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Taschenbuch. Etat : Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 188 pp. Englisch. N� de r�f. du vendeur 9783319142302

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Automatic Design of Decision-Tree Induction Algorithms

Rodrigo C. Barros

Edit� par Springer International Publishing, Springer International Publishing, 2015

ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9783319142302

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Automatic Design of Decision-Tree Induction Algorithms

Rodrigo C. Barros

Edit� par Springer International Publishing Mrz 2015, 2015

ISBN 10 : 3319142305 ISBN 13 : 9783319142302

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9783319142302

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