DETECTING FRAUD WITH MACHINE LEARNING

Don’t take my money boy

Purpose: The purpose of this article is to build and compare the performance of 18 different classifiers in identifying fraudulent credit card transactions.

Materials and methods: The data set contains the credit card transactions made by European card holders for two days of September 2013. Out of the 284,807 transactions…

Frank Ceballos

Physicist | Data Scientist

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