DocumentCode
3144873
Title
An integrated data mining system to automate discovery of measures of association
Author
Chua, Cecil ; Chiang, Roger H L ; Lim, Ee-Peng
Author_Institution
Sch. of Accountacy & Bus., Nanyang Technol. Univ., Singapore
fYear
2000
fDate
4-7 Jan. 2000
Abstract
Many data analysts require tools which can integrate their database management packages (e.g. Microsoft Access) with their data analysis ones (e.g. SAS, SPSS), and provide guidance for the selection of appropriate mining algorithms. In addition, the analysts need to extract and validate statistical results to facilitate data mining. In this paper, we describe an integrated data mining system called the Linear Correlation Discovery System (LCDS) that meets the above requirement. LCDS consists of four major sub-components, two of which, the selection assistant and the statistics coupler, we discussed in this paper. The former examines the scheme and instances to determine appropriate association measurement functions (e.g, chi-square, linear regression, ANOVA). The latter involves the appropriate statistical function on a sample data set, and extracts relevant statistical output such as η2, and R2 for effective mining of data. We also describe a new validation algorithm based on measuring the consistency of mining results applied to multiple test sets.
Keywords
data analysis; data mining; Linear Correlation Discovery System; data analysis; integrated data mining; measures of association; validation algorithm; Analysis of variance; Data analysis; Data mining; Databases; Linear regression; Liquid crystal displays; Packaging; Statistics; Synthetic aperture sonar; Time of arrival estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on
Print_ISBN
0-7695-0493-0
Type
conf
DOI
10.1109/HICSS.2000.926650
Filename
926650
Link To Document