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Neural networks are effective in detecting fraud because
they can:
A. discover new trends since they are inherently linear.
B. solve problems where large and general sets of training
data are not obtainable.
C. attack problems that require consideration of a large
number of input variables.
D. make assumptions about the shape of any curve relating
variables to the output.
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Answer: C
Neural networks can be used to attack problems that require
consideration of numerous input variables, They are capable
of capturing relationships and patterns often missed by
other statistical methods. Neural networks will not discover
new trends. They are inherently nonlinear and make no
assumption about the shape of any curve relating variables
to the output. Neural networks will not work well at solving
problems for which sufficiently large and general sets of
training data are not obtainable.
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