The dataset contains transactions made by credit cards in September by European cardholders, which has 492 frauds out of 284,807 transactions. This is indicated the highly imbalance of the dataset, where frauds ( Class 1) accounts for 0.172% of all transactions. Besides, this only contains numerical variables which are the result of PCA transformation except Time and Amount variables, which can be assumed that the data is scaled. However, there is limitation to explain model decisions ot interpret feature importance in business terms.