Automatic Design of Decision-Tree Induction Algorithms

di Rodrigo C. Barros (Autore)

André C.P.L.F de Carvalho (Autore)

Alex A. Freitas (Autore)

Springer International Publishing AG, 2015

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.

• Autore: Rodrigo C. Barros, André C.P.L.F de Carvalho, Alex A. Freitas
• Editore: Springer International Publishing AG
• Collana: SpringerBriefs in Computer Science
• Anno: 2015
• Rilegatura: Paperback / softback
• Pagine: 176 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319142302

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