Synthetic Data Generator

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Generates realistic synthetic datasets that preserve the statistical properties and relationships of source data without exposing real records. Covers schema-aware generation, correlated and time-series fields, class balancing for ML training, and constraint preservation, with code for tools like SDV, Faker, or custom generators.

使用场景

  • Generating synthetic training data that mirrors real distributions
  • Balancing minority classes for ML models
  • Producing correlated multi-column and time-series data
  • Preserving referential integrity across tables
  • Creating privacy-safe datasets for sharing

示例提示词

Generate synthetic data for an e-commerce schema for ML experimentation.

Tables:
- customers(id, age, region, signup_date)
- orders(id, customer_id, order_date, amount, category)

Requirements:
- Preserve realistic age/amount distributions and customer-order relationships
- 10,000 customers, ~3 orders each
- No real PII

Provide generation code and a short fidelity check.

推荐模型

兼容工具

claude-codecursorkiroany

模态

输入: text, code
输出: code, text

相关 Skills

作者

OpenModels Community

@openmodelsrun