数据加载中.....
|
jsp.display-item.identifier=請使用永久網址來引用或連結此文件:
https://irlib.pccu.edu.tw/handle/987654321/24172
|
| 题名: | An Integral Predictive Model of Financial Distress |
| 作者: | Lee, M (Lee, Mushang)
Wu, TC (Wu, Tsui-Chih) |
| 贡献者: | 財金系 |
| 关键词: | financial-distress-prediction model
stepwise regression
data mining
rough set
decision tree
neural network
logistic regression |
| 日期: | 2012-11 |
| 上传时间: | 2013-02-19 13:23:09 (UTC+8) |
| 摘要: | Traditional statistic models for financial distress are subject to constraints which may lead to imprecise prediction. To contribute to the issue, we construct a two-staged integral model by applying a stepwise regression analysis and a data-mining approach. Specifically, we employ stepwise regression and rough set analysis in feature selection to sieve out variables, and perform decision tree, neural network, and logistic regression analysis to classify firms with financial distress. The findings show that the rates of accuracy for the combinations in descending order are stepwise regression-logistic, stepwise regression-neutral network, stepwise regression-decision tree, rough set theory-neutral network, rough set theory-decision tree, and rough set theory-logistic. |
| 關聯: | JOURNAL OF TESTING AND EVALUATION 卷: 40 期: 6 頁數: 931-938 |
| 显示于类别: | [財務金融學系 ] 期刊論文
|
文件中的档案:
| 档案 |
描述 |
大小 | 格式 | 浏览次数 |
|---|
| index.html | | 0Kb | HTML | 396 | 检视/开启 |
|
在CCUR中所有的数据项都受到原著作权保护.
|
