Pareto-optimality of oblique decision trees from evolutionary algorithms
Journal of Global Optimization
Review: Supervised classification and mathematical optimization
Computers and Operations Research
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The classification problem is of major importance to a plethora of research fields. The outgrowth in the development of classification methods has led to the development of several techniques. The objective of this research is to provide some insight on the relative performance of some well-known classification methods, through an experimental analysis covering data sets with different characteristics. The methods used in the analysis include statistical techniques, machine learning methods and multicriteria decision aid. The results of the study can be used to support the design of classification systems and the identification of the proper methods that could be used given the data characteristics.