Credit Card Fraud Detection

Author(s)	Vishesh Khullar, Arslan Firoz, Gurmeet Singh
Country	India
Abstract	It is important for credit card companies to know see fraudulent credit card sales for customers they are not charged for things they did not buy. Such problems can be dealt with Data Science and its importance, and Mechanical Learning, cannot be skipped. This the project aims to show the modelling data set being used machine learning about Credit Card Fraud Detection. Credit The Problem of Finding Card Fraud involves modelling past debt card transactions and data of those that appear to be such fraud. This model is then used to see if it is new what is being done is fake or not. Our goal here is to find out 100% fake jobs while minimizing categories of fraudulent fraud. Credit Card Fraud Detection a standard sample separation. In this process, we are focused in analysing and prioritizing data sets and the posting of many confusing finding algorithms like this Local Outlier Factor and Isolation Forest algorithm in PCA modified credit card processing data.
Field	Computer
Published In	Volume 6, Issue 2, March-April 2024
Published On	2024-04-16
Cite This	Credit Card Fraud Detection - Vishesh Khullar, Arslan Firoz, Gurmeet Singh - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16655
DOI	https://doi.org/10.36948/ijfmr.2024.v06i02.16655
Short DOI	https://doi.org/gtrfp2

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International Journal For Multidisciplinary Research