Java Deep Learning Cookbook

How it works...

To solve use cases effectively, we need to use the right neural network architecture by determining the problem type. The following are globally some use cases and respective problem types to consider for step 1:

• Fraud detection problems: We want to differentiate between legitimate and suspicious transactions so as to separate unusual activities from the entire activity list. The intent is to reduce false-positive (that is, incorrectly tagging legitimate transactions as fraud) cases. Hence, this is an anomaly detection problem.
• Prediction problems: Prediction problems can be classification or regression problems. For labeled classified data, we can have discrete labels. We need to model data against those discrete labels. ...