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The attached .ipynb file has the complete workflow description of our project on Credit Card Fraud Detection using Machine Learning

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credit-card-fraud-ML

Feature Selection: Pearson Correlation Scatter Plot Visualization Density Plot

Scaling Techniques: Standard Scaler Under sampling

Classification Models used: K Nearest Neighbors Logistic Regression Support Vector Machines Decision Trees Random Forests XGboost LightGBM

Metrics for accuracy of model: ROC-AUC curve Recall Score Classification Report Test Train Split

Contributors: Sumit Kumar Sah Swapnil Jena Rohit Kumar Nayak Shubrato Khumar Shau Siddharth Nanda

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The attached .ipynb file has the complete workflow description of our project on Credit Card Fraud Detection using Machine Learning

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