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Opis

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.§

Szczegóły książki

Kategoria Książki po angielsku Computing & information technology Computer science Artificial intelligence

• Pełny tytuł: Automatic Design of Decision-Tree Induction Algorithms
• Autor: Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex Freitas
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 176
• EAN: 9783319142302
• ISBN: 3319142305
• ID: 09105213
• Wydawca: Springer International Publishing AG
• Waga: 2934 g
• Wymiary: 235 × 155 × 10 mm
• Data wydania: 04. February 2015

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