Outlier detection method based on uncertain data set

Abstract

The invention discloses an outlier detection method based on an uncertain data set and belongs to the technical field of outlier data mining. The method comprises a step 1 of computing the k distance and the k distance neighborhood of each data point in the uncertain data set; a step 2 of computing a probability that a data point q becomes a neighbor of a data point o in the k distance neighborhood; a step 3 of computing the reachable distance of each data point; a step 4 of computing the reachable density of each data point; and a step 5 of computing the outlier factor of each data point in order to determine outlier data. The method may effectively find out outlier data concealed in the uncertain data set.

Description

technical field [0001] The invention relates to the technical field of outlier data mining, in particular to an outlier detection method based on an uncertain data set. Background technique [0002] Outlier data mining technology is one of the research hotspots in the field of data mining at present. The existing outlier data mining is mainly based on the concept of distance or nearest neighbor to determine the outlier mining. With the widespread popularity of the Internet and mobile Internet, a large number of Uncertain data is widely used in different fields such as financial and economic analysis, electronic communication, and modern logistics. The uncertainty of the data itself makes it difficult to accurately judge whether the data is abnormal, which makes it difficult to give exact outlier data. In uncertain data sets, even if a data object itself does not seem to be an outlier, if its degree of uncertainty is very high, the data is likely to be suspected to be abnorma...

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Problems solved by technology

[0002] Outlier data mining technology is one of the research hotspots in the field of data mining at present. The existing outlier data mining is mainly based on the concept of distance or nearest neighbor to determine the outlier mining. With the widespread popularity of the Internet and mobile Internet, a large number of Uncertain data is widely used in different fields such as financial and economic analysis, electronic communication, and modern logistics. The uncertainty of the data itself makes it difficult to accurately judge whether the data is abnormal, which makes it difficult to give exact outlier data

In uncertain data sets, even if a data object itself does not seem to be an outlier, if its uncertainty level is very high, this data is likely to be suspected to be abnormal

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