Abstract
The use of linguistic rulesets is considered one of the greatest advantages that fuzzy classification systems can offer compared to non-fuzzy classification systems. This paper proposes the use of fuzzy thresholds and fuzzy quantifiers for generating linguistic rulesets from a data-driven fuzzy
subsethood-based classification system. The proposed technique offers not only simplicity in the design and
comprehensibility of the generated rulesets but also practicality in the implementation. Additionally, the use of fuzzy quantifiers makes it easier for the user to understand the classification process and how such classifications were reached. The effectiveness of the proposed method is demonstrated using a medical dataset which provides evidence that rules generated by the proposed system are consistent with
the expert-rules created by clinicians.
Original language | English |
---|---|
Title of host publication | Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09) |
Publisher | IEEE Press |
Pages | 1204-1209 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-4244-3597-5 |
ISBN (Print) | 978-1-4244-3596-8 |
DOIs | |
Publication status | Published - Aug 2009 |
Event | Fuzzy Systems - Jeju Island, Korea (Republic of) Duration: 20 Aug 2009 → 24 Aug 2009 Conference number: 18 |
Conference
Conference | Fuzzy Systems |
---|---|
Abbreviated title | FUZZ-IEEE-2009 |
Country/Territory | Korea (Republic of) |
City | Jeju Island |
Period | 20 Aug 2009 → 24 Aug 2009 |