Evaluation & Benchmarks

What problem does it solve?

Streamlines the design and execution of reproducible evaluation benchmarks for brain_ai models, linking rich metrics to actionable insights across cognitive layers.

Core Features & Use Cases

• Standardized metrics suite (accuracy, F1, AUROC, NAB score), per-class breakdowns, confusion matrices, and cross-modality fusion analysis.
• End-to-end benchmark harnesses: deterministic, GPU/CPU-appropriate evaluation loops with synthetic data and self-tests for rapid iteration.
• Reporting and governance: JSON/CSV report generation, baseline comparisons, and delta analysis to monitor progress over time.

Quick Start

Invoke the evaluation harness on synthetic data to generate a baseline benchmark.