Project Info

Project Id:12485

Credit card fraud detection model takes the data from the dataset . It contains only numerical input variables which are the result of a PCA transformation. Features V1, V2, … V28 are the principal components obtained with PCA, the only features which have not been transformed with PCA are 'Time' and 'Amount'. Feature 'Time' contains the seconds elapsed between each transaction and the first transaction in the dataset. The feature 'Amount' is the transaction Amount, this feature can be used for example-dependant cost-sensitive learning. Feature 'Class' is the response variable and it takes value 1 in case of fraud and 0 otherwise.The model takes the dataset and different algorithms are applied on the dataset.The user can see the performace of different modeld on the same dataset.

• Implementation of multiple Algorithms
• Comparison in performance of Algorithms.
• Web based User Interface