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A fuzzy clustering approach to evaluate individual competencies from REFLEX data

机译:一种从REFLEX数据评估个人能力的模糊聚类方法

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摘要

We empirically illustrate how concepts and methods involved in a grade of membership (GoM) analysis can be used to sort individuals by competence. Our study relies on a data set compiled from the international survey on higher education graduates called REFLEX. We focus on the subset of data related to the perception of own competencies. It is first decomposed into fuzzy clusters that form a hierarchical fuzzy partition. Then, we calculate a scalar measure of competencies for each fuzzy cluster, and subsequently use the individual GoM scores to combine cluster-based competencies to position individuals on a scale from 0 to 1.
机译:我们从经验上说明会员资格等级(GoM)分析中涉及的概念和方法如何用于按能力对个人进行排序。我们的研究依赖于国际高等教育毕业生REFLEX收集的数据集。我们专注于与自身能力感知有关的数据子集。首先将其分解为模糊聚类,形成层次化的模糊分区。然后,我们为每个模糊聚类计算能力的标量度量,然后使用单个GoM分数组合基于聚类的能力以将个体定位在从0到1的范围内。

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