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

Volume

2

fYear

2010

fDate

11-12 May 2010

Firstpage

313

Lastpage

314

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICICTA.2010.787

Filename

5523398