You are creating a new experiment in Azure Machine Learning Studio. The training set has a significant class imbalance, with one class having far fewer observations than the others. You need to choose a suitable data sampling strategy to address this imbalance.

Solution: You use the Stratified split for the sampling mode.

Does this solution meet the goal?