ACRES: A framework for (semi)automatic generation of rule‐based expert systems with uncertainty from datasets

Traditionally, the design of an expert system involves acquiring knowledge, in the form of symbolic rules, directly from the expert(s), which is a complex and time‐consuming task. Although expert systems approach is quite old, it is still present, especially where explicit knowledge representation a...

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Bibliographic Details
Published in:Expert systems 2024-12, Vol.41 (12), p.n/a
Main Authors: Kovas, Konstantinos, Hatzilygeroudis, Ioannis
Format: Article
Language:English
Subjects:
certainty factors
Datasets
Decision trees
expert system generation
Expert systems
Explicit knowledge
Knowledge representation
Machine learning
rule extraction
supervised learning
Uncertainty
uncertainty representation
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