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Applying Variable Precision Rough Set for Clustering Diabetics Dataset

机译:将可变精度粗糙集应用于糖尿病数据集

摘要

Computational models of the artificial intelligence such as rough set theory have several applications. Rough set-based data clustering can be considered further as a technique for medical decision making. This paper presents the results of an experimental study of a rough-set based clustering technique using Variable Precision Rough Set (VPRS). Here, we employ our proposed clustering technique [12] through a medical dataset of patients suspected diabetic. Our results indicate that the VPRS-based technique is better than that the standard rough set-based techniques in the process of selecting a clustering attribute.
机译:诸如粗糙集理论之类的人工智能计算模型具有多种应用。基于粗糙集的数据聚类可以进一步考虑作为医疗决策技术。本文介绍了使用可变精度粗糙集(VPRS)的基于粗糙集的聚类技术的实验研究结果。在这里,我们通过对疑似糖尿病患者的医学数据集采用了我们提出的聚类技术[12]。我们的结果表明,在选择聚类属性的过程中,基于VPRS的技术优于基于标准粗糙集的技术。

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