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

机译:应用异常检测方法对分类质量的影响

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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.
机译:本文介绍了删除异常值的过程之前和之后的一些所选的异常检测方法和分类测试质量的比较。在几个所选数据集上使用一些选定的异常检测方法,执行消除非典型数据的过程。非典型数据可能是各种性质。它可以是噪音或可以是不正确的数据。但是,它们也可以是正确的数据,因为某种原因与典型数据不同。去除非典型数据可能对分类质量具有不同的影响。它可能取决于消除异常数据的使用方法,还可以取决于使用数据的性质。因此,对原始数据以及移除的异常值进行分类过程。比较和讨论得到的结果。

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