Unlimited

Authorized users

Can lend chapters, not whole ebooks

Automatic Design of Decision-Tree Induction Algorithms [electronic resource] / Rodrigo C. Barros, André C.P.L.F. de Carvalho, Alex A. Freitas.

9783319142319 electronic book
3319142313 electronic book
9783319142302

Cham [Switzerland] : Springer, [2015]

English

1 online resource.

10.1007/978-3-319-14231-9 doi

QA76.9.A43 B37 2015eb

005.1

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.

Includes bibliographical references.

Access limited to authorized users.

SpringerBriefs in computer science.

Print version: 9783319142302

Online Resources > Ebooks
All Resources