Clean, well-labeled datasets used for machine learning are partitioned into three subsets: Training sets, Validation sets, and Test sets. As your team is doing this, what's the best way to split up this data?
- Split by patterned subsampling
- Split by random subsampling
- Use the same data for all sets
- Split by alphabetical order
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