✂ Split Dataset

Split a 3LC table into train, validation, and test sets — creating new table revisions with full lineage tracking.

Stratified
Balanced class distribution
Full Lineage
EditedTable revisions
Reproducible
Seeded random splits
1 Select table
2 Set ratios
3 Split
Split Configuration
Select the table you want to split into train/val/test sets.
Stratified sampling ensures each split has the same class ratio as the original.
70%
20%
10%
70%
20%
10%
Total: 100% — drag sliders to adjust. Train + Val + Test must equal 100%.
Fixed seed for reproducible splits. Change to get a different random ordering.
How It Works

EditedTable revisions: Each split creates a new table revision (EditedTable) that references the original rows — no data is duplicated.

Stratified sampling: When enabled, the split preserves the class distribution from the original table in each split. Requires a categorical label column.

DAG lineage: All split tables appear as children of the source table in the DAG view, making the relationship clear.