CAJ | 학술논문

为了有效地评估客户的可信度，提高信贷机构经济效益。文中通过统计学中的参数方法Logistic回归和非参数方法分类树这两种方法，建立两种模型对数据进行预测，应用SPSS软件的Binary Logistic Regression方法，利用ROC曲线的性质来对模型的性能进行评价，根据输出结果比较两种模型在应用中都是可行有效的，在实际操作中应因地制宜，把握两种方法的优势，得到更有价值的结果。
위료유효지평고객호적가신도，제고신대궤구경제효익。문중통과통계학중적삼수방법Logistic회귀화비삼수방법분류수저량충방법，건립량충모형대수거진행예측，응용SPSS연건적Binary Logistic Regression방법，이용ROC곡선적성질래대모형적성능진행평개，근거수출결과비교량충모형재응용중도시가행유효적，재실제조작중응인지제의，파악량충방법적우세，득도경유개치적결과。
The study aims to effectively evaluate the customer credibility and improve the economic benefits of credit mechanism .By their methods of Logistic regression and classification tree ,two kinds of models were established to forecast data .Their performance was evaluated by the Binary Logistic Regression method of SPSS software and the properties of the ROC curve .The output results show that both models are feasible and effective .In practice ,the advantages of the two methods should be taken to get more valuable results .