Machine Learning based Data Mining for Detection of Credit Card Frauds

This research study analyzes the different data mining techniques used for the detection of credit card frauds. Additionally, different data mining techniques are properly described in this study. The steps of data mining are clearly explained in this study, which are helpful for recognizing the fraudulent activities. This study is discussing that Bayesian network, and decision tree are the effective techniques of data mining. The issues of data mining are also discussed in this study, which is creating performance issues, and user interaction issues in the financial institutions. Therefore, this study is providing the importance of RF algorithm in the determination of the credit card fraud. Data cleaning, and data visualization, therefore, the machine learning process is allowed to be developed with the support of the data mining process of credit cards. Clustering is the main process that is takes place in this data mining process. Additionally, the sequential pattern is being highlighted by this process, which helps to improve the fraud detection process of credit cards.