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Automatic Design of Decision-Tree Induction Algorithms (Springerbriefs in Computer Science)
Rodrigo C. Barros; André C. P. L. F. De Carvalho; Alex A. Freitas (Author)
·
Springer
· Paperback
Automatic Design of Decision-Tree Induction Algorithms (Springerbriefs in Computer Science) - Rodrigo C. Barros; André C. P. L. F. De Carvalho; Alex A. Freitas
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Synopsis "Automatic Design of Decision-Tree Induction Algorithms (Springerbriefs in Computer Science)"
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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The book is written in English.
The binding of this edition is Paperback.
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