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An improved density-based outlier mining algorithm
一种改进的基于密度的离群数据挖掘算法

Keywords: data mining,outlier,density-based
数据挖掘
,离群数据,基于密度,改进,基于密度,离群数据,挖掘算法,algorithm,outlier,mining,速度,数据集,快速,数据测试,二维空间,判断,邻域,利用

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Abstract:

Based on the characteristic that outliers are not included in the appointed neighborhood of inliers, an improved algorithm for outlier mining was proposed. Data was judged whether it was included in the appointed neighborhood of inliers firstly. If the answer was negative, the number of data that was included in the appointed neighborhood was counted. Experimental results show that the improved algorithm is effective and efficient in outlier mining and it is faster than the original algorithm.

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