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Attribute transformations for data mining I: Theoretical explorations

✍ Scribed by Tsau Young (T.Y.) Lin

Publisher: John Wiley and Sons
Year: 2002
Tongue: English
Weight: 80 KB
Volume: 17
Category: Article
ISSN: 0884-8173
DOI: 10.1002/int.10017

No coin nor oath required. For personal study only.

✦ Synopsis

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 patterns to visible states. (2) There are no apparent hints from the raw data as to what transformations could be employed; domain experts need to be in the loop of data mining. (3) All transformations can be expressed, or more precisely approximated, by polynomials. Such expressions provide some means for a brute force search (one degree at a time) of the transformations. A reasonable success in a linear case (degree one) is reported in Ref. 2.

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