A data scientist has produced two models for a single machine learning problem.

Ensemble learning is a machine learning technique that involves combining several models to solve a particular problem. The scenario described fits the concept of ensemble learning, where two models, each performing well under different conditions, are combined to create a more robust model. This approach often leads to better performance as it combines the strengths of multiple models.

References

Introduction to Ensemble Learning: https://machinelearningmastery.com/ensemble-machine-learning-algorithms-python-scikit-learn/