A comparative assessment of classification methods

A comparative assessment of classification methods

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Article ID: iaor2004917
Country: Netherlands
Volume: 35
Issue: 4
Start Page Number: 441
End Page Number: 454
Publication Date: Jul 2003
Journal: Decision Support Systems
Authors:
Keywords: artificial intelligence: decision support
Abstract:

Classification systems play an important role in business decision-making tasks by classifying the available information based on some criteria. The objective of this research is to assess the relative performance of some well-known classification methods. We consider classification techniques that are based on statistical and AI techniques. We use synthetic data to perform a controlled experiment in which the data characteristics are systematically altered to introduce imperfections such as nonlinearity, multicollinearity, unequal covariance, etc. Our experiments suggest that data characteristics considerably impact the classification performance of the methods. The results of the study can aid in the design of classification systems in which several classification methods can be employed to increase the reliability and consistency of the classification.

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