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Fuzzy decision tree based analysis of databases

Beynon, Malcolm James 2008. Fuzzy decision tree based analysis of databases. In: Galindo, José ed. Handbook of research on fuzzy information processing in databases, Hershey, PA: IGI Global, pp. 760-783. (10.4018/978-1-59904-853-6.ch031)

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Abstract

The general fuzzy decision tree approach encapsulates the benefits of being an inductive learning technique to classify objects, utilising the richness of the data being considered, as well as the readability and interpretability that accompanies its operation in a fuzzy environment. This chapter offers a description of fuzzy decision tree based research, including the exposition of small and large fuzzy decision trees to demonstrate their construction and practicality. The two large fuzzy decision trees described are associated with a real application, namely, the identification of workplace establishments in the United Kingdom that pay a noticeable proportion of their employees less than the legislated minimum wage. Two separate fuzzy decision tree analyses are undertaken on a low-pay database, which utilise different numbers of membership functions to fuzzify the continuous attributes describing the investigated establishments. The findings demonstrate the sensitivity of results when there are changes in the compactness of the fuzzy representation of the associated data

Item Type: Book Section
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information: 2 volumes
Publisher: IGI Global
ISBN: 9781599048536
Related URLs:
Last Modified: 04 Jun 2017 03:38
URI: http://orca-mwe.cf.ac.uk/id/eprint/24022

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