Credit Card Fraud Detection Using KNC, SVC, and Decision Tree Machine Learning Algorithms

Credit cards are replacing cash in shopping. With the increase in popularity of plastic money like credit cards, hackers are misusing this as an opportunity to commit fraud. In this research work, we have used three different machine-learning techniques to detect credit card fraud. We have taken a credit card fraud dataset from Kaggle and applied K Neighbor Classifiers (KNC), Support Vector Classifiers (SVC), and decision tree machine-learning methods to this dataset. We have achieved $\mathbf{9 9. 9 4 \%}$ accuracy using both KNN and Decision Tree machine learning algorithms. We have got $\mathbf{9 9. 8 4 \%}$ accuracy using the Support vector classifier (SVC) machine learning Algorithm.