Title :
Data mining application for upgrading quality of wine production
Author :
Tian, Haishan ; Pang, Qiaohong
Author_Institution :
Economic Inf. Eng. Sch., Southwestern Univ. of Finance & Econ., Chengdu, China
Abstract :
We propose a data mining approach to predict the wine´s quality level in order to improve the quality of products for wine enterprises in this paper. A large dataset is considered and three regression techniques were applied. Through the comparison, we get the conclusion that the model established by neural network is more accurate and it can improve the quality of wine´s production.
Keywords :
data mining; neural nets; production engineering computing; regression analysis; wine industry; data mining; neural network; regression techniques; wine enterprises; wine production quality; Accuracy; Adaptation model; Artificial neural networks; Biological system modeling; Data mining; Data models; Predictive models; Data mining; Model selection; Neural network; Regression; wine´s quality;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis (ICACIA), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8025-8
DOI :
10.1109/ICACIA.2010.5709862
