It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
The dataset 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. It contains features V1 to V28 which are the principal components obtained by PCA. We are going to neglect the time feature which is of no use to build the models. The remaining features are the ‘Amount’ feature that contains the total amount of money being transacted and the ‘Class’ feature that contains whether the transaction is a fraud case or not.
This dataset it taken from Kaggle. https://www.kaggle.com/mlg-ulb/creditcardfraud