Influence of the Applied Outlier Detection Methods on the Quality of Classification

Abstract

This paper presents a comparison of a few chosen outlier detection methods and test quality of classification, both before and after the procedure of removing outliers. Using a few selected methods of outlier detection on several selected data sets, the process of elimination of atypical data was carried out. Atypical data may be of various nature. It can be noise or can be incorrect data. However, they can also be correct data, which for some reason are different from typical data. The removal of non-typical data may have a different effect on the classification quality. It may be dependent on the used method of removing unusual data but also on the nature of used data. Therefore, the classification process was carried out on the original data as well as with the outliers removed. The obtained results were compared and discussed.