Company Growth Ability Prediction in Chinese Real Estate Industry
Corporate growth is one of the most researched subjects in different areas of economic science. The ability of growth has usually been considered an essential objective for a firm,contributing to its survival and competitiveness. Real estate industry has been one of the shoring industries for Chinese economic growth. The growth of Real Estate companies depends on their performance. Predicting Real Estate companies growth ability accurately and efficiently is very important. This paper analyzes the use of decision tree for Real Estate companies growth ability. Linear models,although simple and easy to interpret,require statistical assumptions which may be unrealistic;meanwhile,neural networks are usually too complicated to comprehend. Decision trees are not only able to discriminate patterns which are not linearly separable,but also can be easily understood. In this paper,an algorithm is proposed to select dilation and translation parameters that yield a decision tree classifier with good parsimony characteristics. The prediction model is built in a case study,and the results,supported by a test study,show that decision trees may be a valid model to predict listed Real Estate companies growth ability in China.
growth real estate industry decision tree prediction
Qin zheng Jiang Yanhui
School of Information Management and Engineering,Shanghai University of Finance and Economics,Shangh School of Information Management and Engineering,Shanghai University of Finance and Economics,Shangh
国际会议
The First International Conference on Management Innovation(ICMI 2007)(管理创新会议)
上海
英文
954-958
2007-06-04（万方平台首次上网日期，不代表论文的发表时间）