Lab: Classify Using Frequency-Severity Modeling

On this mission, you'll use a strategy called Frequency-Severity modeling to classify fraudulent credit card transactions. You’ll create a blender model and compare models using the Model Comparison tool. 

Mission format and duration: self-paced, hands-on, 1 hour

Upon completion of this mission, you will be able to: 

• Build a fraud-detection regression model using Frequency-Severity modeling
• Compare modeling algorithms using the Model Comparison and Feature Insights tools
• Create a blender model

Who should complete this mission?

• Business Analysts
• Citizen Data Scientists
• Data Scientists

Before embarking on this mission, you should complete one of the following:

• Starter Quest appropriate for your role (self-paced mission)
• AutoML I (virtual instructor-led mission)
• DataRobot for Data Scientists (virtual instructor-led mission)

Technical requirements

• Chrome browser
• DataRobot Automated Machine Learning — If you don’t have access to the application, please sign up for our free trial: datarobot.com/trial.