Credit Card Fraud Detection on the Skewed Data Using Various Classification and Ensemble Techniques

A. Mishra, Chaitanya Ghorpade
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引用次数: 37

Abstract

Nowadays, as internet speed has increased and the prices of mobile have decreased very much in past few years. Also the data prices too are very much affordable to most of the people. This has resulted into the digitization of most of the institutes as it is easy and convenient for the people and also for the authority to maintain the records. So, it resulted in most of the banks and other institutes receiving and transferring money through credit cards. But with the hackers and other cyber criminals around there is always chances of the frauds in the transactions. The possibility of the fraud transaction is very less but it is not negligible and even having one fraud transaction is unacceptable because it is crime and we can’t neglect it even if it is very less as it harms both the customer and credibility of the institute. So this paper aims at analyzing various classification techniques using various metrics for judging various classifiers. This model aims at improving fraud detection rather than misclassifying a genuine transaction as fraud.
基于不同分类和集成技术的偏斜数据信用卡欺诈检测
如今,随着互联网速度的提高,移动设备的价格在过去几年里下降了很多。此外,数据价格对大多数人来说也是负担得起的。这导致了大多数研究所的数字化,因为这对人们和当局来说都很容易和方便地保存记录。因此,它导致大多数银行和其他机构通过信用卡接收和转账。但随着黑客和其他网络犯罪分子的出现,交易中总是有欺诈的机会。欺诈交易的可能性非常小,但也不容忽视,即使有一次欺诈交易也是不可接受的,因为这是犯罪,我们不能忽视它,即使它非常小,因为它损害了客户和机构的信誉。因此,本文旨在分析各种分类技术,使用各种度量来判断各种分类器。该模型旨在改进欺诈检测,而不是将真实交易错误地分类为欺诈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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