DocumentCode :
988116
Title :
Induction of meta-knowledge about knowledge discovery
Author :
Gaines, B.R. ; Compton, P.
Author_Institution :
Knowledge Sci. Inst., Calgary Univ., Alta., Canada
Volume :
5
Issue :
6
fYear :
1993
fDate :
12/1/1993 12:00:00 AM
Firstpage :
990
Lastpage :
992
Abstract :
A study is reported of the use of ripple-down rule induction to develop a metamodel of ten years of clinical data captured as part of the development of an expert system for thyroid diagnosis. It is shown how the suitability for inductive knowledge discovery from such real-world data can be characterized in terms of its stationarity, and how the best error rates achievable and the amount of data necessary to achieve them can be estimated
Keywords :
inference mechanisms; learning (artificial intelligence); medical administrative data processing; medical diagnostic computing; medical expert systems; Garvan thyroid database; clinical data; error rates; expert system; induct; inductive knowledge discovery; knowledge discovery; machine learning; medical diagnosis; meta-knowledge induction; meta-modeling; metamodel; real-world data; ripple-down rule induction; rules with exceptions; thyroid diagnosis; Australia Council; Computer science; Databases; Diagnostic expert systems; Error analysis; Knowledge based systems; Machine learning; Metamodeling; Out of order; Predictive models;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.250084
Filename :
250084
Link To Document :
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