Automatic Design Decision Tree Induction by Barros Rodrigo (14 results)

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Paperback. Condition: Brand New. 2015 edition. 188 pages. 9.00x6.00x0.50 inches. In Stock.

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Taschenbuch. Condition: Neu. Automatic Design of Decision-Tree Induction Algorithms | Rodrigo C. Barros (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | xii | Englisch | 2015 | Springer | EAN 9783319142302 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condition: 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.…

Condition: New. Print on Demand 190.

Condition: New. PRINT ON DEMAND 190.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 188 pp. Englisch.…