Predict_Fraudulent_Transactions

Team Members

• Ananya Thomas
• Amrita Bhatia

This project compares the performance of four machine learning models in a binary classification problem for prediction fraudulent transactions.The models compared are:

Logistic Regression Naive-Bayes K-nearest neighbours Decision tree

Outcome

On comparing the four models the accuracy of the Decison tree model is found to be the best followed by K-Nearest neighboursand then Logistic Regression. Naive Bayes is found to have the least accuracy.