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A PROMETHEE-based classification method using concordance and discordance relations and its application to bankruptcy prediction

机译:基于PROMETHEE的一致性和不一致性关系分类方法及其在破产预测中的应用

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摘要

Outranking relation theory has been widely used to study pattern classification. Here we propose a classification method with concepts from the flows used in PROMETHEE methods, which are extensively applied in multi-criteria decision aids. PROMETHEE uses a flow, generated on the basis of a preference index and measured by various preference functions for each criterion, to represent the preference intensity for one pattern over another pattern. However, only criteria that are concordant with the preference contribute to a preference index. In the present study, the opinions from discordant criteria are also taken into account. The proposed method newly defines an overall preference index using both concordance and discordance relations for ordinal sorting problems. The final classification decision for a new pattern depends on its net flow. The criteria weights are determined using a genetic-algorithm- based approach. Empirical results obtained for a real-world problem regarding bankruptcy prediction demonstrate that the proposed method performs well compared to other well-known classification methods.
机译:超越关系理论已被广泛用于研究模式分类。在这里,我们提出了一种分类方法,该方法利用了PROMETHEE方法中使用的流程的概念,这些方法已广泛应用于多准则决策辅助工具中。 PROMETHEE使用基于优先级索引生成并通过各种优先级函数对每个标准进行测量的流来表示一个模式相对于另一模式的优先级强度。但是,只有符合偏好的标准才有助于偏好索引。在本研究中,还考虑了来自不一致标准的意见。所提出的方法使用序数排序问题的一致性和不一致关系重新定义了总体偏好指数。新模式的最终分类决定取决于其净流量。使用基于遗传算法的方法确定标准权重。针对有关破产预测的实际问题获得的经验结果表明,与其他众所周知的分类方法相比,所提出的方法表现良好。

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