Automatic Design of Decision-Tree Induction Algorithms

von Rodrigo C. Barros, André C.P.L.F de Carvalho, Alex A. Freitas

176 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: SpringerBriefs in Computer Science
• Themen: Informatik und Informationstechnologie Datenbanken / Datenmanagement Data Mining
• ISBN: 9783319142302
• Sprache: Englisch
• Erscheinungsdatum: 03.03.2015
• Größe: 23.5 x 15.5 cm
• Verlag: Springer International Publishing