Building Combined Classifiers.

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:Faculty of Science and Technology
ID Code:8501
Deposited On:19 Dec 2008 19:01
Last Modified:10 Sep 2014 15:43

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