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Comparison of Different Calculations of the Density-Based Local Outlier Factor

机译:基于密度的局部异常因素因子的不同计算的比较

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In the paper, we propose several new density-based algorithms for outlier detection. We present the detailed synoptic theoretical analysis of the algorithms that compute the local outlier factor as a function of the densities of the neighborhood of the objects in a set of objects. Based on this analysis we propose a new calculation of the radius of the neighborhood and we create 66 algorithms to compute the outlier factor. All the algorithms are tested in the complex experiments to describe their basic and also specific characteristics. The results are presented and discussed. Intuitively it seems that the way how the radius of the neighborhood is calculated is important. This idea led to numerous modifications of this part of the algorithms, but on the basis of the experiments we demonstrate that these modifications have only little influence, and we describe which part of the algorithms influence the outlier score the most and we recommend three generally applicable algorithms with specific characteristics.
机译:在本文中,我们提出了几种新的基于密度的算法进行了异常检测。我们介绍了将本地异常因素因子计算为一组对象中对象邻域的密度的函数的算法的详细的算法理论分析。基于此分析,我们提出了一个新的邻域半径的​​新计算,我们创建了66个算法来计算异常因子。在复杂的实验中测试所有算法,以描述它们的基本和特定特征。结果呈现和讨论。直观地似乎,计算邻域的半径是如何计算的。这个想法导致了这一部分的算法的许多修改,但在实验的基础上,我们证明这些修改只有很小的影响,我们描述了算法的哪一部分影响了最高的分数,我们推荐三个通常适用三个具有特定特性的算法。

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