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Balancing accuracy, complexity and interpretability in consumer credit decision making: A C-TOPSIS classification approach

机译：平衡消费者信贷决策中的准确性，复杂性和可解释性：C-TOPSIS分类方法

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摘要

Accuracy, complexity and interpretability are very important in credit classification. However, most approaches cannot perform well in all the three aspects simultaneously. The objective of this study is to put forward a classification approach named C-TOPSIS that can balance the three aspects well. C-TOPSIS is based on the rationale of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). TOPSIS is famous for reliable evaluation results and quick computing process and it is easy to understand and use. However, it is a ranking approach and three challenges have to be faced for modifying TOPSIS into a classification approach. C-TOPSIS works out three strategies to overcome the challenges and retains the advantages of TOPSIS. So C-TOPSIS is deduced to have reliable classification results, high computational efficiency and ease of use and understanding. Our findings in the experiment verify the advantages of C-TOPSIS. In comparison with 7 popular approaches on 2 widely used UCI credit datasets, C-TOPSIS ranks 2nd in accuracy, 1st in complexity and is in 1st rank in interpretability. Only C-TOPSIS ranks among the top 3 in all the three aspects, which verifies that C-TOPSIS can balance accuracy, complexity and interoretabilitv well.
机译：准确性，复杂性和可解释性在信用分类中非常重要。但是，大多数方法不能同时在这三个方面都表现良好。这项研究的目的是提出一种可以很好地平衡这三个方面的分类方法C-TOPSIS。 C-TOPSIS基于TOPSIS（类似于理想解决方案的订单优先技术）的基本原理。 TOPSIS以可靠的评估结果和快速的计算过程而闻名，易于理解和使用。但是，这是一种排名方法，将TOPSIS修改为分类方法必须面对三个挑战。 C-TOPSIS制定了三种策略来克服挑战并保留TOPSIS的优势。因此，推论C-TOPSIS具有可靠的分类结果，高计算效率以及易于使用和理解。我们在实验中的发现证实了C-TOPSIS的优势。与2个广泛使用的UCI信用数据集上的7种流行方法相比，C-TOPSIS的准确性排名第二，复杂性排名第一，可解释性排名第一。在这三个方面中，只有C-TOPSIS排在前三位，这证明C-TOPSIS可以很好地平衡准确性，复杂性和互用性。

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  • 来源
    《Knowledge-Based Systems》 |2013年第11期|258-267|共10页
  • 作者

    Xiaoqian Zhu; Jianping Li; Dengsheng Wu; Haiyan Wang; Changzhi Liang;

  • 作者单位

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China,University of Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China;

    Jiangsu Province Institute of Quality & Safety Engineering, Nanjing 210046, China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China,University of Chinese Academy of Sciences, Beijing 100190, China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Credit scoring; TOPSIS; Credit classification; Credit risk; Support vector machine; Bank risk evaluation;

    机译：信用评分;TOPSIS;信用分类;信用风险;支持向量机;银行风险评估;

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