Credit card fraud detection system.
Date:
- Project description: Developed an SVM model from scratch for classification of fraudulent credit card transactions on a dataset taken from Kaggle.
- Objective : Training Support Vector Machine for detecting Credit card fraud using given data.
- Method Used: 200 samples are randomly take from the data file (100 each for positive and negative class) five times.
- Trained the Model 5 times and obtained respective accuracies using 80% of the data for training and 20% for testing split.
- Achieved accuracy of 92.5% by formulating an algorithm for convex quadratic optimization problem of dual form of SVM.
- cvxopt library has been used for finding out the optimum solution for Lagrange Multipliers.