Your project overview:- Fraud detection methods are continuously developed to defend criminals in adapting to their fraudulent strategies.This project covers credit card fraud and is meant to look at a dataset of transactions and predict whether it is fraudulent or not.

Problem statement:- Detecting credit card frauds.

Solution applied:- This data is fit into a model and the following outlier detection modules are applied on it: • Local Outlier Factor • Isolation Forest

Random Forest algorithm 

Results:- For each algorithm is given in the output as follows, where class 0 means the transaction was determined to be valid and 1 means it was determined as a fraud transaction.

Isolation Forest: 17
Accurancy Score : 0.9974842767295597


Local Outlier Factor: 21
Accurancy Score : 0.9974842767295597

Conclusion:- The algorithm does reach over 99.7% accuracy

Any references used :- google.com kaggle.com