Abstract
a variety of machine learning techniques to a
difficult modelling problem, the spatial distribution
of an endangered Australian marsupial, the southern
brown bandicoot (Isoodon obesulus). Four learning
techniques decision trees/rules, neural networks,
support vector machines and genetic programming were
applied to the problem. Support vector and neural
network approaches gave marginally better predictivity,
but in the context of low overall accuracy, decision
trees and genetic programming gave more useful results
because of the human comprehensibility of their
models.
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