abstract = "This paper explores the use of genetic programming to
evolve fuzzy rules for the purpose of fraud detection.
The fuzzy rule evolver designed during this research is
described in detail. Four key system evaluation
criteria are identified: intelligibility, speed,
handling noisy data, and accuracy. Three sets of
experiments are then performed in order to assess the
performance of different components of the system, in
terms of these criteria. The paper concludes: 1. that
many factors affect accuracy of classification, 2.
intelligibility and processing speed mainly seem to be
affected by the fuzzy membership functions and 3. noise
can cause loss of accuracy proportionate to the square
notes = "GECCO-99LB, fraud detection, pre-GP 3-way clustering
of each attribute multi-objective fitness function.
variable size tree genotypes, bitstring in tree
specifies input field, start small. Newer version
Iris and Wisconsin Breast Cancer. Perfomance falls
lineraly or quadratically with noise.",