Biomedical Engineering Reference
In-Depth Information
Chapter XX
The Exposition of
Fuzzy Decision Trees and
Their Application in Biology
Malcolm J. Beynon
Cardiff University, UK
Kirsty Park
University of Stirling, UK
AbSTRACT
This chapter employs the fuzzy decision tree classification technique in a series of biological based
application problems. With its employment in a fuzzy environment, the results, in the form of fuzzy 'if ..
then ..' decision rules, bring with them readability and subsequent interpretability. The two contrasting
applications considered concern, the age of abalones and the lengths of torpor bouts of hibernating
Greater Horseshoe bats. Emphasis is on the visual results presented, including the series of membership
functions used to construct the linguistic variables representing the considered attributes and the final
fuzzy decision trees constructed. Technical details presented further offer the opportunity to readers to
future employ the technique in other biological applications.
INTRODUCTION
the utilisation of FST in such development has
been with the inclusion of the acknowledgement
of the presence of vagueness and ambiguity dur-
ing its operation. Further, it has also invoked the
ability to interpret the structuring and subsequent
results from data analysis in a linguistic orientated
language (Grzegorzewski and Mrówka, 2005).
Indeed, artificial intelligence, with respect to FST,
is closely associated with the mimicry of human
Fuzzy set theory (FST) stands out as a general
methodology that has contributed to the devel-
opment of already established techniques used
throughout many areas of science, including
biology and medicine (recent examples include,
Morato
et al
., 2006; Mastorocostas and Theocha-
ris, 2007). Since its introduction in Zadeh (1965),
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