Credit Card Fraud Detection System using several methods of Anomaly detection with Probability Densities.
We will use Local Outlier Factor and Isolation Forest algorithms to detect credit card fraud. The data set used has 492 frauds out of 284,807 transactions, we will detect them using our unsupervised ML algorithms.
- Get the dataset given by Machine Learning Group of ULB : https://www.kaggle.com/mlg-ulb/creditcardfraud#creditcard.csv
- Install the libraries : numpy, pandas, matplotlib, seaborn, sklearn