Title :
Data Systematic Purifying Analysis in Data Mining
Author :
Cheng, Yu-Ting ; Shia, Ben-Chang ; Kuo, Jun-Yuan ; Yang, Hui-Ru
Author_Institution :
Dept. of Stat. Sci., Nat. Chengchi Univ., Taipei, Taiwan
fDate :
March 31 2009-April 2 2009
Abstract :
A goal database and an auxiliary database utilizing functional mapping make the database combine as a great database, then imputes the missing data or the rare data missing in the database. In order to improve the data analysis efficiency, this research proposed the data SPA (data systematic purifying analysis) to purify the data systematically. This research has applied three kinds of methods to evaluate the data. After the process of the data SPA, it can be easily understand that the data SPA really has good effect on data mining, because it can increase the amount of information of the data and improve the data evaluation efficiency.
Keywords :
data analysis; data mining; database management systems; auxiliary database; data SPA; data analysis efficiency; data mining; data systematic purifying analysis; functional mapping; missing data; Boosting; Classification tree analysis; Computer science; Data analysis; Data mining; Databases; Decision trees; Diseases; Predictive models; Statistical analysis; Data mining; Systematic purifying analysis;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.908
