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计算机应用 2007
An improved density-based outlier mining algorithm
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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.