AI Component Evaluation Dashboard

Real-time indicators tracking system classification, matching precision, and rule verification compliance[cite: 252].

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4.1 Needs Classification Performance [cite: 255]

Model Accuracy [cite: 257]
92.4% ↑ 1.2%

Overall correct needs classification[cite: 261].

Precision (Mean) [cite: 262]
90.1%

Validity of identified priority classes[cite: 263].

Recall Tracking [cite: 266]
89.5%

Captured cases out of actual needs[cite: 267].

Balanced F1-Score [cite: 270]
89.8%

Harmonic mean indicator metric[cite: 271, 272].

4.2 Recommendation & Matching Execution Quality [cite: 277]

Top-1 Matching Relevance [cite: 278]

Current: 85.0% Acceptable Target: 80%+

Percentage where the #1 ranked mentor matches expert evaluation or is selected[cite: 279, 282].

Rule Compliance Verification Rate [cite: 298]

Current constraint fit: 100% Strict Boundary

Ensures zero matches breach systemic constraints like mentor overload boundaries[cite: 203, 302].

Live Preprocessing Engine Status Report [cite: 93]

Stale/Duplicate Records Filtered [cite: 81, 83] 1
Median Imputations Run [cite: 90] 2