Title :
Financial Data Mining Based on Support Vector Machines and Ensemble Learning
Author :
Lei, Shi ; Xinming, Ma ; Lei, Xi ; Xiaohong, Hu
Author_Institution :
Coll. of Inf. & Manage. Sci., HeNan Agric. Univ., Zhengzhou, China
Abstract :
With the rapid development of e-commerce, financial data mining has been one of the most important research topics in the data mining community. Support vector machines (SVMs) and ensemble learning are two popular techniques in the machine learning field. In this paper, support vector machines and ensemble learning are used to classify financial data respectively. The experiments conducted on the public dataset show that compared with SVMs, ensemble learning achieves obvious improvement of performance.
Keywords :
data mining; financial data processing; learning (artificial intelligence); pattern classification; support vector machines; SVM; e-commerce; ensemble learning; financial data mining; machine learning; support vector machine; Automation; Boosting; Data mining; Learning systems; Machine learning; Machine learning algorithms; Pattern recognition; Risk management; Support vector machine classification; Support vector machines; Ensemble Learning; Financial Data Mining; Support Vector Machines;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.787
