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