Eastwood, M. and Gabrys, B., 2008. Building Combined Classifiers. In: Nguyen, N.T., Kolaczek, G. and Gabrys, B., eds. Knowledge Processing and Reasoning for Information Society. Warsaw, Poland: EXIT Publishing House, pp. 139-163.
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This chapter covers different approaches that may be taken when building an ensemble method, through studying specific examples of each approach from research conducted by the authors. A method called Negative Correlation Learning illustrates a decision level combination approach with individual classifiers trained co-operatively. The Model level combination paradigm is illustrated via a tree combination method. Finally, another variant of the decision level paradigm, with individuals trained independently instead of co-operatively, is discussed as applied to churn prediction in the telecommunications industry.
|Item Type:||Book Section|
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
Generalities > Computer Science and Informatics
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||INVALID USER|
|Deposited On:||19 Dec 2008 19:01|
|Last Modified:||07 Mar 2013 15:02|
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