Beynon, Malcolm James ![]() |
Abstract
The utilization of a fuzzy aspect within data analysis attempts to move from a quantitative to a more qualitative investigative environment. As such, this may allow the more non-quantitative researchers results they can use, based on sets of linguistic terms. In this paper an inductive fuzzy decision tree approach is utilized to construct a fuzzy-rule-based system for the first time in a biological setting. The specific biological problem considered attempts to identify the antecedents (conditions in the fuzzy decision rules) which characterize the length of song flight of the male sedge warbler when attempting to attract a mate. Hence, for a non-quantitative investigator the resultant set of fuzzy rules allows an insight into the linguistic interpretation on the relationship between associated characteristics and the respective song flight duration.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Biosciences Business (Including Economics) |
Subjects: | H Social Sciences > H Social Sciences (General) Q Science > QA Mathematics |
Uncontrolled Keywords: | classification; fuzzy decision trees; membership functions; sedge warblers; song flight |
Publisher: | Wiley-Blackwell |
ISSN: | 1468-0394 |
Last Modified: | 08 Aug 2024 13:50 |
URI: | https://orca.cardiff.ac.uk/id/eprint/37939 |
Citation Data
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