DocumentCode
3190347
Title
The application of C4.5 algorithm based on SMOTE in financial distress prediction model
Author
Chang, Zi-nan
Author_Institution
Dept. of Inf. Technol., Jinling Inst. of Technol., Nanjing, China
fYear
2011
fDate
8-10 Aug. 2011
Firstpage
5852
Lastpage
5855
Abstract
Datasets used in financial distress forecast are unbalanced. The traditional method gets lower predict accuracy especially in small samples of unbalanced datasets. The datasets are balanced with SMOTE method and then classified with the classical decision tree algorithm C4.5. The results show that the prediction model based on C4.5 algorithm gets the better performance.
Keywords
data mining; decision trees; financial management; C4.5 algorithm; SMOTE method; decision tree algorithm; financial distress prediction model; Accuracy; Algorithm design and analysis; Classification algorithms; Decision trees; Machine learning; Prediction algorithms; Predictive models; Decision Tree; financial distress prediction; smote; unbalanced dataset;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location
Deng Leng
Print_ISBN
978-1-4577-0535-9
Type
conf
DOI
10.1109/AIMSEC.2011.6011460
Filename
6011460
Link To Document