Abstract
Classification methods use different algorithms to get better performance in research fields such as statistics, machine learning and computational analysis. This study reviews the traditional method, recursive partitioning, as well as newer classification algorithms, conditional inference tree and evolutionary tree. Variations and improvements in algorithms, data types with or without missing values, and special applications are widely used in this field. Although classification algorithms have been studied often and performed reasonably well, there is no existing one that performs best among the others. Using a real dataset, the classification methods under consideration are applied and the results are compared.
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Asfha, H.D., Kan Kilinc, B. (2018). Appraisal of Performance of Three Tree-Based Classification Methods. In: Tez, M., von Rosen, D. (eds) Trends and Perspectives in Linear Statistical Inference . Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-73241-1_3
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DOI: https://doi.org/10.1007/978-3-319-73241-1_3
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