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03024nam a22004935i 4500 |
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978-3-319-14231-9 |
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DE-He213 |
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20151030201108.0 |
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150204s2015 gw | s |||| 0|eng d |
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|a 9783319142319
|9 978-3-319-14231-9
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|a 10.1007/978-3-319-14231-9
|2 doi
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|d GrThAP
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|a QA76.9.D343
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|a UNF
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|a UYQE
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|a COM021030
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|a 006.312
|2 23
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|a Barros, Rodrigo C.
|e author.
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|a Automatic Design of Decision-Tree Induction Algorithms
|h [electronic resource] /
|c by Rodrigo C. Barros, André C.P.L.F de Carvalho, Alex A. Freitas.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a XII, 176 p. 18 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Computer Science,
|x 2191-5768
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|a 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.
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|a 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.
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|a Computer science.
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|a Data mining.
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|a Pattern recognition.
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|a Computer Science.
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|a Data Mining and Knowledge Discovery.
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|a Pattern Recognition.
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|a de Carvalho, André C.P.L.F.
|e author.
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|a Freitas, Alex A.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319142302
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|a SpringerBriefs in Computer Science,
|x 2191-5768
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856 |
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|u http://dx.doi.org/10.1007/978-3-319-14231-9
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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950 |
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|a Computer Science (Springer-11645)
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