Agent skill
splitting-datasets
Split datasets into training, validation, and test partitions with the right stratification and temporal rules. Use as a narrow preprocessing helper once the broader ML workflow is already chosen, not as the main route owner for an end-to-end ML task.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/splitting-datasets-foryourhealth111-pix-vibe-skills
SKILL.md
Dataset Splitter
Positioning
Treat this skill as a narrow helper for partition strategy.
When to Use
Use this skill when:
- Prepare a dataset for machine learning model training.
- Create training, validation, and testing sets.
- Partition data to evaluate model performance.
Not For / Boundaries
- Full preprocessing-pipeline ownership: use
preprocessing-data-with-automated-pipelines - Leakage audits and prediction-time checks: use
ml-data-leakage-guard - Model training and tuning after the split: use
training-machine-learning-models
Typical Outputs
- Partition strategy with ratios, random seeds, and stratification rules
- Notes on temporal or grouped split constraints
- Handoff guidance for leakage review and downstream training
Related Skills
preprocessing-data-with-automated-pipelinesfor the broader preprocessing sequenceml-data-leakage-guardto verify the split does not leak future or test information
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