دانلود مقاله ISI انگلیسی شماره 41649
عنوان فارسی مقاله

کشف کلاه برداری کارت اعتباری با تجزیه و تحلیل تشخیصی اصلاح شده فیشر

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
41649 2015 7 صفحه PDF سفارش دهید 5300 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Detecting credit card fraud by Modified Fisher Discriminant Analysis
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 42, Issue 5, 1 April 2015, Pages 2510–2516

کلمات کلیدی
جعل کارتهای اعتباری - تفکیک خطی - تابع تفکیک خطی فیشر - تشخیص اصلاح شده فیشر - سودآوری
پیش نمایش مقاله
پیش نمایش مقاله کشف کلاه برداری کارت اعتباری با تجزیه و تحلیل تشخیصی اصلاح شده فیشر

چکیده انگلیسی

In parallel to the increase in the number of credit card transactions, the financial losses due to fraud have also increased. Thus, the popularity of credit card fraud detection has been increased both for academicians and banks. Many supervised learning methods were introduced in credit card fraud literature some of which bears quite complex algorithms. As compared to complex algorithms which somehow over-fit the dataset they are built on, one can expect simpler algorithms may show a more robust performance on a range of datasets. Although, linear discriminant functions are less complex classifiers and can work on high-dimensional problems like credit card fraud detection, they did not receive considerable attention so far. This study investigates a linear discriminant, called Fisher Discriminant Function for the first time in credit card fraud detection problem. On the other hand, in this and some other domains, cost of false negatives is very higher than false positives and is different for each transaction. Thus, it is necessary to develop classification methods which are biased toward the most important instances. To cope for this, a Modified Fisher Discriminant Function is proposed in this study which makes the traditional function more sensitive to the important instances. This way, the profit that can be obtained from a fraud/legitimate classifier is maximized. Experimental results confirm that Modified Fisher Discriminant could eventuate more profit.

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