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Attribute transformations for data mining I: Theoretical explorations
Author(s) -
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.10017
Subject(s) - computer science , domain (mathematical analysis) , degree (music) , transformation (genetics) , feature (linguistics) , data mining , raw data , theoretical computer science , mathematics , mathematical analysis , biochemistry , chemistry , physics , linguistics , philosophy , acoustics , gene , programming language
Abstract Attribute (feature) transformations on databases are examined from a data mining prospect.Theoretical examples from classical mathematics are used to illustrate the effects of the transformations:(1) Certain examples show that attribute transformations are the only means to bring out the patternsto visible states. (2) There are no apparent hints from the raw data as to what transformations couldbe employed; domain experts need to be in the loop of data mining. (3) All transformations can beexpressed, or more precisely approximated, by polynomials. Such expressions provide some means for a brute forcesearch (one degree at a time) of the transformations. A reasonable success in a linear case(degree one) is reported in Ref. 2. © 2002 John Wiley & Sons,Inc.