Induction of Meta-Knowledge About Knowledge Discovery

Authors:
B. R. Gaines;P. Compton
Affiliations:
-;-
Venue:
IEEE Transactions on Knowledge and Data Engineering
Year:
1993

Citing 6
Cited 1

Simplifying decision trees

International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Knowledge in context: a strategy for expert system maintenance

AI '88 Proceedings of the second Australian joint conference on Artificial intelligence
A philosophical basis for knowledge acquisition

Knowledge Acquisition
An ounce of knowledge is worth a ton of data: quantitative studies of the trade-off between expertise and data based on statistically well-founded empirical induction

Proceedings of the sixth international workshop on Machine learning
Knowledge Discovery in Databases

Knowledge Discovery in Databases
What's So Bad About Rule-Based Programming?

IEEE Software

Knowledge acquisition: Past, present and future

International Journal of Human-Computer Studies

Quantified Score

Hi-index	0.00

Visualization

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.