SA-240_Refactor_LabelAccuracy_Class

[marklondon999]

📌 Pull Request Template

I want to refactor the LabelAccuracy class by subdividing its responsibilities into distinct components  
so that the codebase is easier to maintain, test, and extend for future evaluation workflows.

Description:
The current LabelAccuracy class handles multiple responsibilities including data preprocessing, validation, accuracy computation, and visualisation.

This refactor will involve breaking the class into smaller, purpose-specific modules or methods, such as:

Preprocessing: Handling input formatting, missing values, and column setup.
Accuracy Evaluation: Computing full and 2-digit match accuracy, Jaccard similarity, etc.
Visualisation: Generating plots, heatmaps, and summary displays.

Acceptance Criteria:

[ ] LabelAccuracy is refactored into clearly defined subcomponents or methods.
[ ] Each component has a single, well-defined responsibility.
[ ] Unit tests are updated or added for each new component.
[ ] No change in output or evaluation results from the original implementation.
[ ] Code is peer reviewed and merged.

✅ Checklist

Please confirm you've completed these checks before requesting a review.

• Code is formatted using Black
• Imports are sorted using isort
• Code passes linting with Ruff, Pylint, and Mypy
• Security checks pass using Bandit
• API and Unit tests are written and pass using pytest
• Terraform files (if applicable) follow best practices and have been validated (terraform fmt & terraform validate)
• DocStrings follow Google-style and are added as per Pylint recommendations
• Documentation has been updated if needed

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