What is the name of the data set used to apply the predictive model in order to produce new predictions?

• A. Scoring
• B. Training
• C. Validation
• D. Testing

Answer: (A)

The main idea here is the stage where you take a trained model and use it to generate predictions on new data. That step is called scoring, and the data you feed into the model to produce those new predictions is the scoring data. Scoring is what you do once the model is ready to be deployed, producing outputs for fresh observations. The other terms refer to model-building or evaluation phases: training data is used to fit the model, validation data helps tune its parameters, and testing data assesses performance on unseen data. So scoring is the correct name for applying the model to produce new predictions.