[Feature] early_stop AA test

[tikhomirovd]

🚀 Feature Proposal

Implement Early Stopping in AA Tests

Motivation

After conducting research on early stopping criteria in AA tests, the next step is to implement a robust early stopping mechanism. This feature will help optimize the runtime of AA tests by stopping iterations when convergence is detected, leading to more efficient resource usage and faster experiment completion.

Feature Description

• Implement early stopping logic in the AA testing framework based on RnD findings.
• Ensure that early stopping is an optional feature that can be enabled or disabled by the user.
• Integrate stopping criteria such as confidence interval stabilization, sequential testing, or other statistical methods.
• Provide configuration options for users to set custom thresholds for early stopping.
• Update experiment logs and reporting to indicate when early stopping occurs.

Potential Impacts

• Reduced computation time for AA tests while maintaining statistical accuracy.
• Increased efficiency in large-scale experiment deployments.
• More flexible experimentation with adaptive iteration control.

Alternatives

• Keep the current implementation without early stopping (longer but stable testing).
• Use a predefined fixed iteration limit without dynamic stopping (less adaptive).

Additional Context

• Ensure compatibility with existing AA test structures.
• Provide comprehensive documentation and example use cases.
• Add unit tests to validate early stopping logic across different datasets.

Checklist

• Implement early stopping logic in the AA test framework.
• Allow users to enable or disable early stopping.
• Add configuration options for stopping criteria.
• Integrate logging and reporting for early stopping events.
• Write unit tests covering early stopping behavior.
• Update documentation with usage guidelines.
• Review and refine implementation before merging.