Credit Card Fraud Detection using Random Forest Algorithm

Technological developments have changed the way we live.Banks have introduced the concept of credit cards.Due to the advancement in the electronic commerce technology, the use of credit cards has increased and it has become a popular mode of payment for both online and offline purchases.In spite of this enormous popularity the cards are not free of risk.However, the vast majority of learning algorithms that have been proposed for fraud detection rely on assumptions that hardly hold in a real-world fraud-detection system.Our project mainly focussed on credit card fraud detection in real world.Initially we will collect the credit card datasets for trained dataset.Then we will provide the user credit card queries for testing data set.After classification process of dataset random forest algorithm is used for analysing data set and current dataset provided by the user.After final optimization the results indicates about the optimal accuracy for Random Forest Algorithm is 98.6% of the accuracy of the result data.