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• W1776817391 abstract "The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision treebased algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models." @default.
• W1776817391 created "2016-06-24" @default.
• W1776817391 creator A5072014150 @default.
• W1776817391 date "2008-01-01" @default.
• W1776817391 modified "2023-09-27" @default.
• W1776817391 title "Data Mining Techniques in Fraud Detection" @default.
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• W1776817391 doi "https://doi.org/10.15394/jdfsl.2008.1040" @default.
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