Computer Science ›› 2008, Vol. 35 ›› Issue (12): 192-195.

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TAO Yun-xin PI De-chang (College of Information Science and Teehnology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,Chian)   

  • Online:2018-11-16 Published:2018-11-16

Abstract: Most density-based outlier detection algorithms require the setting of two input parameters and are sensitive to input parameters. Incorrect setting may cause an algorithm to fail in finding all meaningful outliers and even find wrong outliers, which cann

Key words: Data mining, Outlier detection, Parameter, Neighborhood,Density

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