Automatic Design of Decision-Tree Induction Algorithms
Springer International Publishing (Verlag)
978-3-319-14230-2 (ISBN)
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.
Introduction.- Decision-Tree Induction.- Evolutionary Algorithms and Hyper-Heuristics.- HEAD-DT: Automatic Design of Decision-Tree Algorithms.- HEAD-DT: Experimental Analysis.- HEAD-DT: Fitness Function Analysis.- Conclusions.
| Erscheint lt. Verlag | 3.3.2015 |
|---|---|
| Reihe/Serie | SpringerBriefs in Computer Science |
| Zusatzinfo | XII, 176 p. 18 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 296 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Automatic Design • decision trees • evolutionary computation • hyper-heuristics • machine learning |
| ISBN-10 | 3-319-14230-5 / 3319142305 |
| ISBN-13 | 978-3-319-14230-2 / 9783319142302 |
| Zustand | Neuware |
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