Attribute Transformations on Numerical Databases. Applications to Stock Market and Economic Data

Authors:
Tsau Young Lin;Joseph Tremba
Affiliations:
-;-
Venue:
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Year:
2000

Citing 1
Cited 1

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Database Mining on Derived Attributes

TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing

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Abstract

The effects of attribute transformations on numerical data mining are investigated. Theoretical examples from classical mathematics are used to illustrate its critical-ness. The simplest kind of attribution transformations, linear transformations, is applied to stock market and economic data. Some useful "predictive" rules are generated. Here "predictive" is used in the sense that the logical patterns involve time elements.