A Machine Learning Project
Credit card fraud is a wide-ranging term for theft and fraud committed using or involving a payment card,
such as a credit card or debit card, as a fraudulent source of funds in a transaction. It is of importance
to detect such fraud via some novel methods. Here we will apply several machine learning algorithms to make prediction.
The datasets(https://www.kaggle.com/dalpozz/creditcardfraud) contains transactions made
by credit cards in September 2013 by european cardholders.
This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions.
The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.
I test Logistic Regression on skewed data. I also apply cross validation for hyperparameter tuning
different classification models. My model is offering an 99% accuracy score on the data.
You can see all the codes in the jupyter notebook.