DATA MINING TECHNIQUES

Institution UNIVERSITY
Course FORENSICS
Year 1st Year
Semester Unknown
Posted By Brian Mike
File Type pdf
Pages 21 Pages
File Size 545.18 KB
Views 5296
Downloads 0
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Description

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
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