The Apply of Data Mining in Financial Distress Prediction Model of Logistics Companis
Follow the development of information technology, data mining tools has been more and more applications in all areas of life. And the results have been made to improve the efficiency of peoples lives. In this paper, we apply principal factor analysis and decision tree analysis in data mining in analysis of the financial early warning. First, according to the idea of dimension reduction, we use principal factor analysis to extract the composite indicator from indicator system of financial distress prediction model. According to the cumulative contribution rate of 85％, we set the number of public factor as six. This is a qualitative analysis. Then we set whether the companys net profit growth as target and set six composite indicators as property to do decision tree analysis. Through decision tree analysis we can find the most important indicators and the range of the indicator to achieve measurable results. Ultimately, we will provide decision makers with qualitative and quantitative analysis to forecast whether the company can achieve net profit growth through financial indicators.
principal factor analysis decision tree analysis financial distress prediction model
Gu Yu Guo Wenjuan
Beijing Wuzi University Beijing, China 101149
国际会议
重庆
英文
735-738
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）