What term describes assigning a prediction to new records using a model?

Study for the Predictive Analytics Modeler Explorer Test with multiple-choice questions, hints, and explanations. Prepare confidently for your certification exam!

Multiple Choice

What term describes assigning a prediction to new records using a model?

Explanation:
The term that describes assigning a prediction to new records using a model is scoring. In the context of predictive analytics, scoring involves applying a trained model to new data to generate predictions or estimates based on the patterns and relationships learned during the model training phase. Scoring is a critical step in the predictive modeling process as it helps in evaluating how well the model performs on unseen data. After a model has been developed and validated to ensure its effectiveness, it can then be used to score new records, providing insights or predictions that inform decision-making. The result of scoring is typically a numeric value or class label that represents the model's prediction regarding the new observations. In summary, scoring is essential for leveraging the capabilities of a predictive model, as it allows for practical application and utilization of the model's output in real-world scenarios.

The term that describes assigning a prediction to new records using a model is scoring. In the context of predictive analytics, scoring involves applying a trained model to new data to generate predictions or estimates based on the patterns and relationships learned during the model training phase.

Scoring is a critical step in the predictive modeling process as it helps in evaluating how well the model performs on unseen data. After a model has been developed and validated to ensure its effectiveness, it can then be used to score new records, providing insights or predictions that inform decision-making. The result of scoring is typically a numeric value or class label that represents the model's prediction regarding the new observations.

In summary, scoring is essential for leveraging the capabilities of a predictive model, as it allows for practical application and utilization of the model's output in real-world scenarios.

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