# Classification Dataset Stratified Split Review and Handoff

Prepare independent classification records, freeze a seeded stratified split, review class coverage and leakage limits, and deliver verified partitions with a reproducibility ledger.

> Canonical page: https://elysiatools.com/en/hubs/classification-dataset-stratified-split-review-and-handoff

- **Keywords:** classification dataset split workflow, stratified train validation test, dataset leakage review, reproducible split handoff

## Frequently asked questions

### Does a fixed seed make this identical to scikit-learn?

No. Reproduction needs the same input order, fields, settings and implementation version. This tool uses its own random generator; the same numeric seed does not imply identical output in another library.

### Does no duplicate warning mean no leakage?

No. The built-in check compares complete row contents. Different IDs, near copies, repeated entities and future-derived features can evade it; retain separate membership and domain review.

### Does the SMOTE preview change the exported CSVs?

No. The split tool shows numeric-feature examples from training data; its split CSVs still contain the original assigned rows. Review feature suitability and implement any approved augmentation separately.

### Can two rare-class records populate three partitions?

No. Passing the minimum check does not ensure every class appears everywhere. Inspect actual counts and change data collection or the evaluation design with approval.

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