SynthEval: A Novel Open-Source Machine Learning Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data

 SynthEval: A Novel Open-Source Machine Learning Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data

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SynthEval: A Novel Open-Source Machine Learning Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data

Utilize SynthEval to access advanced evaluation of synthetic tabular data, ensuring detailed utility and privacy analysis. The framework offers practical solutions for AI-driven decision-making and product development.

Key Features and Value

  • Enables easy and consistent evaluation of synthetic tabular data
  • Provides a large collection of metrics for user-specific benchmarks
  • Supports custom metrics without editing the source code
  • Allows simultaneous evaluation of multiple synthetic renditions of the same dataset
  • Addresses the challenge of maintaining consistency with fluctuating data types

Practical Implementation

Enhance your company’s AI capabilities with SynthEval to stay competitive and redefine your way of work. Identify automation opportunities, define KPIs, select AI solutions, and implement gradually to drive measurable impacts on business outcomes.

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