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Attribute transformations for data mining II: Applications to economic and stock market data
Author(s) -
Tremba Joseph,
Lin Tsau Young T.Y.
Publication year - 2002
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10018
Subject(s) - stock market , computer science , data mining , data science , geography , archaeology , context (archaeology)
The effects of attribute transformations have been examined theoretically in part I of this article. This ispart II, and its focus is on applications. Specific linear transformations, which have statistical meaning, areapplied to a selected set of economic and stock market data. The data are selected from the computer,semiconductor, and semiconductor equipment industries. The main data mining tool is the rough set basedsoftware, DataLogic/R+, augmented with programs that perform linear transformations, conceptgeneralization, and so on. Some useful “predictive” rules are discovered. Here,“predictive” is used in the sense that the logical patterns involve time elements. We should notethat even in such simple cases, a trail‐and‐error approach is necessary for finding the righttransformation. © 2002 John Wiley & Sons, Inc.