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Roughness and granularity measures using Hausdorff metric: a new approach

机译:使用Hausdorff度量的粗糙度和粒度度量:一种新方法

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摘要

Measures for uncertainty due to approximation of sets in rough set theory are accuracy and roughness. In determining these quantities, the cardinality of a set is always used and never the numerical values of the attributes (if they exist) of elements in the sets. Therefore, distances between the exact set and the corresponding upper and lower approximations can give a better quantitative measure of the roughness. Here, we propose a measure based on Hausdorff metric which takes into account the distance between two sets, the exact set and its two approximations (lower and upper). Using this measure, we can quantify the uncertainty of a rough set based on the values in the domain of sample points but not on the basis of number of sample points. Also, we propose a new measure for granulation which is again based on the Hausdorff metric. The effectiveness of the proposed measures is demonstrated on a synthetic data.
机译:在粗糙集理论中,由于近似集而导致的不确定性的度量是精度和粗糙度。在确定这些数量时,始终使用集合的基数,而不使用集合中元素的属性的数值(如果存在)。因此,精确集与相应的上下近似之间的距离可以更好地定量测量粗糙度。在这里,我们提出了一种基于Hausdorff度量的度量,该度量考虑了两个集合之间的距离,精确集合及其两个近似值(下限和上限)。使用此度量,我们可以基于采样点域中的值而不是采样点数量来量化粗糙集的不确定性。另外,我们提出了一种新的制粒方法,该方法再次基于Hausdorff指标。综合数据证明了拟议措施的有效性。

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