An Ensemble Method for Medicine Best Selling Prediction

Author

Xiang, Chengguan ; Chen, Mei ; Wang, Hanhu

Author_Institution

Comput. Sci. & Technol. Dept., Guizhou Univ., Guiyang, China

Volume

1

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

100

Lastpage

103

Abstract

In this paper the author presents a data mining model based ensemble methodology in medicine selling prediction. The ANN algorithm is utilized for feature selection, and some machine learning techniques are constructed for ensemble model in medicine best selling and best sell season prediction. The verification is conducted on the real cases from GuiYang ZhiFuTang Pharmacy Company Sell data which consists of 63044 records and 17 fields. The real case experiments show that, our approach works effectively and could be used as an assistant approach for selling analysis in some circumstances.

Keywords

data mining; feature extraction; neural nets; pharmaceutical industry; artificial neural network algorithm; data mining model; ensemble method; feature selection; machine learning technique; medicine best selling prediction; Data mining; Databases; Decision making; Fuzzy systems; Input variables; Machine learning; Machine learning algorithms; Prediction algorithms; Predictive models; Stability; Data Mining; Ensemble; Prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3735-1

Type

conf

DOI

10.1109/FSKD.2009.245

Filename

5358643