How to improve our Fraud prediction model created using Keras Neural Networks?
My team and I are developing a workflow to predict e-commerce fraud. Our dataset has 5% of transactions classified as fraud and we want to train a Fraud prediction model based on Non-Fraud Transactions. Using the Keras Neural Network we obtained the following results but we would like to know if you have any suggestions on how we can improve our results.
We have already done some research and applied this workflow (Keras Autoencoder for Fraud Detection - Training – KNIME Community Hub)