A confidence voting process for ranking problems based on support vector machines

A confidence voting process for ranking problems based on support vector machines

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Article ID: iaor200937802
Country: Germany
Volume: 166
Issue: 1
Start Page Number: 23
End Page Number: 38
Publication Date: Feb 2009
Journal: Annals of Operations Research
Authors: , ,
Keywords: datamining
Abstract:

In this paper, we deal with ranking problems arising from various data mining applications where the major task is to train a rank-prediction model to assign every instance a rank. We first discuss the merits and potential disadvantages of two existing popular approaches for ranking problems: the ‘Max-Wins’ voting process based on multi-class support vector machines (SVMs) and the model based on multi-criteria decision making. We then propose a confidence voting process for ranking problems based on SVMs, which can be viewed as a combination of the SVM approach and the multi-criteria decision making model. Promising numerical experiments based on the new model are reported.

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