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.
npx skills add foryourhealth111-pixel/Vibe-Skills --skill splitting-datasets --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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` -
What does the splitting-datasets skill do?
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.
How do I install it?
Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill splitting-datasets --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.