Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The fraud loss for selecting the model complexity in fraud detection   In fraud detection applications, the investigator is typically limited to
controlling a restricted number k of cases. The most efficient manner of
allocating the resources is then to try selecting the k cases with the highest
probability of being fraudulent. The prediction model used for this purpose
must normally be regularized to avoid overfitting and consequently bad
prediction performance. A new loss function, denoted the fraud loss, is
proposed for selecting the model complexity via a tuning parameter. A
simulation study is performed to find the optimal settings for validation.
Further, the performance of the proposed procedure is compared to the most
relevant competing procedure, based on the area under the receiver operating
characteristic curve (AUC), in a set of simulations, as well as on a VAT fraud
dataset. In most cases, choosing the complexity of the model according to the
fraud loss, gave a better than, or comparable performance to the AUC in terms
of the fraud loss.

25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
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The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
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The categories of this paper are: solv-int
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The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph