C2090-930 · Question #59
You have optimized four models that do not meet your performance goals. You believe that by merging these models together you would achieve better performance. Which node would allow you to…
The correct answer is D. Ensemble node. An Ensemble node combines multiple models into a single, stronger predictive model by aggregating their outputs - exactly the scenario described, where merging underperforming models can yield better collective performance than any individual model alone. The Aggregate node…
Question
You have optimized four models that do not meet your performance goals. You believe that by merging these models together you would achieve better performance. Which node would allow you to accomplish this task?
Options
- AAggregate node
- BReclassify node
- CRegression node
- DEnsemble node
How the community answered
(43 responses)- A2% (1)
- B2% (1)
- D95% (41)
Explanation
An Ensemble node combines multiple models into a single, stronger predictive model by aggregating their outputs - exactly the scenario described, where merging underperforming models can yield better collective performance than any individual model alone. The Aggregate node summarizes or groups data records (like averaging rows), not models. The Reclassify node remaps categorical values to new categories and has nothing to do with model combination. The Regression node builds a single predictive model for continuous outcomes - it creates a model, it doesn't merge them.
Memory tip: Think "ensemble cast" - just as a movie ensemble brings together many actors to create a stronger performance than one actor alone, an Ensemble node brings together many models to improve prediction.
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