Data pre-processing by genetic algorithms for bankruptcy prediction

Chih Fong Tsai, Jui Sheng Chou

研究成果: 書貢獻/報告類型會議論文篇章同行評審

11 引文 斯高帕斯(Scopus)

摘要

Bankruptcy prediction has been approached by data mining techniques. However, since data pre-processing including feature selection or dimensionality reduction and data reduction is a very important stage for successful data mining, very few consider performing both tasks to examine the impact of data pre-processing on prediction performance. This paper applies genetic algorithms, which have been widely used for the data pre-processing tasks, for feature selection and data reduction over a public bankruptcy prediction dataset. In particular, the experiments based on different priorities of performing feature selection and data reduction are conducted. The results show that performing data reduction only can allow the support vector machine (SVM) classifier to provide the highest rate of prediction accuracy. However, executing both feature selection and data reduction with different priorities performs the same. They not only largely reduce the dataset size, but also keep the similar performance as SVM without data pre-processing.

原文???core.languages.en_GB???
主出版物標題IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
頁面1780-1783
頁數4
DOIs
出版狀態已出版 - 2011
事件IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 - Singapore, Singapore
持續時間: 6 12月 20119 12月 2011

出版系列

名字IEEE International Conference on Industrial Engineering and Engineering Management
ISSN(列印)2157-3611
ISSN(電子)2157-362X

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
國家/地區Singapore
城市Singapore
期間6/12/119/12/11

指紋

深入研究「Data pre-processing by genetic algorithms for bankruptcy prediction」主題。共同形成了獨特的指紋。

引用此