Abstract:The outlier detection is to select uncommon data from a data set, which can significantly improve the quality of results for the data mining algorithms. A typical feature of the outliers is that they are always far away from a majority of data in the data set. In this paper, we present a graph-based outlier detection algorithm named INOD, which makes use of this feature of the outlier. The DistMean-neighborhood is used to calculate the cumulative in-degree for each data. The data, whose cumulative in-degree is… Show more
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