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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/19491

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Title
An Application of time-changing feature selection
Related
Williams, Graham J. and Simoff, Simeon J.. Data mining : theory, methodology, techniques and applications, p.203-217
DOI
10.1007/11677437_16
Related
Lecture notes in computer science : lecture notes in artificial intelligence 3755
Publisher
Berlin, Germany : Springer
Date
2006
Author/Creator
Zhang, Yihao
Author/Creator
Orgun, Mehmet A
Author/Creator
Lin, Weiqiang
Author/Creator
Graco, Warwick
Description
This paper describes a time-changing feature selection1 framework based on hierachical distribution method for extracting knowledge from health records. In the framework, we propose three steps for time-changing feature selection. The first step is a qualitative-based search, to find qualitative features (or, structural time-changing features). The second step performs a quantitative-based search, to find quantitative features (or, value time-changing features). In the third step, the results from the first two steps are combined to form hybrid search models to select a subset of global time-changing features according to a certain criterion of medical experts. The present application of the time-changing feature selection method involves time-changing episode history, an integral part of medical health records and it also provides some challenges in time-changing data mining techniques. The application task was to examine time related features of medical treatment services for diabetics. This was approached by clustering patients into groups receiving similar patterns of care and visualising the features devised to highlight interesting patterns of care.
Description
15 page(s)
Subject Keyword
time-changing data mining
Subject Keyword
event sequence
Subject Keyword
time-changing feature selection
Subject Keyword
hierarchical distribution
Subject Keyword
health records
Resource Type
book chapter
Organisation
Macquarie University. Dept. of Computing

Identifier
http://hdl.handle.net/1959.14/19491
Identifier
ISBN:9783540325475
Identifier
ISSN:1611-3349
Identifier
mq-rm-2006002896
Language
eng
Save/E-mail Citation
Citation Format
E-mail Address
Subject
"Data mining : theory, methodology, techniques and applications"
 
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