scholarly journals Machine Learning Approach on Apache Spark for Credit Card Fraud Detection

2020 ◽  
Vol 25 (1) ◽  
pp. 101-106
Author(s):  
Thakur Santosh ◽  
Dharavath Ramesh
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Fraud Detection ◽  
Apache Spark ◽  
Learning Approach ◽  
Credit Card Fraud ◽  
Machine Learning Approach

scholarly journals Credit Card Fraud Detection System

2020 ◽  
Vol 6 (12) ◽  
pp. 24-27
Author(s):  
Shashank Singh and Meenu Garg
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Data Science ◽  
Detection System ◽  
Fraud Detection ◽  
Detection Problem ◽  
Credit Card Fraud ◽  
Local Outlier Factor ◽  
Local Outlier ◽  
Isolation Forest

It is essential that Visa organizations can distinguish false Mastercard exchanges so clients are not charged for things that they didn't buy. Such issues can be handled with Data Science and its significance, alongside Machine Learning, couldn't be more important. This undertaking expects to outline the demonstrating of an informational collection utilizing AI with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem incorporates demonstrating past Visa exchanges with the information of the ones that ended up being extortion. This model is then used to perceive if another exchange is fake. Our target here is to identify 100% of the fake exchanges while limiting the off base misrepresentation arrangements. Charge card Fraud Detection is an average example of arrangement. In this cycle, we have zeroed in on examining and pre- preparing informational indexes just as the sending of numerous irregularity discovery calculations, for example, Local Outlier Factor and Isolation Forest calculation on the PCA changed Credit Card Transaction

Machine Learning for Credit Card Fraud Detection

2021 ◽  
Author(s):  
Yuxin Gao ◽  
Shuoming Zhang ◽  
Jiapeng Lu ◽  
Yuxin Gao ◽  
Shuoming Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Fraud Detection ◽  
Credit Card Fraud
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