By Kartik Goel
In Credit Card Fraud Detection, I used different machine learning algorithms to check for fraudulent activities of a card in Python.
As we are moving towards a digital only economy, it is imperative for computerized exchanges to be secured. The issue is that with these quickly expanding exchanges, the odds of fake exchanges are likewise on their height.
I am utilizing the distinctive AI calculations like Logistic Regression, Naive Bayes, K Nearest Neighbor, and so on and ascertain the accuracy with these one by one.
This dataset contains three relevant columns, which are Amount, Class, and Time.
The other 28 columns are modified into PCA (Principal Component Analysis) to save customer recognition
I cleaned and prepared the dataset, plotted the graphs, divided the dataset into trainng and testing and then went on to apply the three algorithms Logistic Regression, Naive Bayes and KNN and found out the accuracy of all three.
Submitted by Kartik Goel (6395)
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