Individual skill
splitting-datasets
Process split datasets into training, validation, and testing sets for ML model development. Use when requesting "split dataset", "train-test split", or "data partitioning". Trigger with relevant phrases based on skill purpose.
skills/.curated/splitting-datasets/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Last checked
- Nov 12, 2026
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- Repository last updated
- Nov 12, 2026
- License
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- ai Declared skill tag
- testing Declared skill tag
- ml Declared skill tag
- testing Derived category
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SKILL.mdcore · 3,344 bytesassets/README.mddoc · 308 bytesassets/dataset_schema.jsonasset · 2,915 bytesassets/example_dataset.csvasset · 668 bytesassets/split_data_config.yamlasset · 1,797 bytesreferences/README.mddoc · 59 bytesscripts/README.mddoc · 302 bytes
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# Dataset Splitter
Split datasets into training, validation, and testing sets with configurable ratios and stratification options.
## Overview
This skill automates the process of dividing a dataset into subsets for training, validating, and testing machine learning models. It ensures proper data preparation and facilitates robust model evaluation.
## How It Works
1. **Analyze Request**: The skill analyzes the user's request to determine the dataset to be split and the desired proportions for each subset.
2. **Generate Code**: Based on the request, the skill generates Python code utilizing standard ML libraries to perform the data splitting.
3. **Execute Splitting**: The code is executed to split the dataset into training, validation, and testing sets according to the specified ratios.
## When to Use This Skill