{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/kb-2026-00282",
  "headline": "Model Evaluation Metrics",
  "description": "Model evaluation metrics quantify performance. Classification: accuracy, precision, recall, F1-score, ROC-AUC. Regression: MSE, MAE, R². Confusion matrix: TP/FP/FN/TN. Choose metrics aligned with business goals: medical diagnosis needs high recall (miss fewer positives), spam detection needs high precision (fewer false alarms).",
  "dateCreated": "2026-05-22T14:59:47.499Z",
  "dateModified": "2026-05-22T14:59:47.499Z",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "human_only",
  "citation": []
}