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What is Condition Attribute

Handbook of Research on Fuzzy Information Processing in Databases
It is an attribute that describes an object. Within a decision tree it is part of a nonleaf node, so it performs as an antecedent in the decision rules used for the final classification of an object.
Published in Chapter:
Fuzzy Decision-Tree-Based Analysis of Databases
Malcolm Beynon (Cardiff University, UK)
Copyright: © 2008 |Pages: 24
DOI: 10.4018/978-1-59904-853-6.ch031
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.
Full Text Chapter Download: US $37.50 Add to Cart
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Fuzzy Decision Trees
An attribute that describes an object. Within a decision tree it is part of a non-leaf node, so performs as an antecedent in the decision rules used for the final classification of an object.
Full Text Chapter Download: US $37.50 Add to Cart
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