{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/kb-2026-00276",
  "headline": "Overfitting and Regularization",
  "description": "Overfitting occurs when a model learns noise and patterns specific to training data, failing to generalize to unseen data. Signs: low training error, high validation error. Regularization techniques prevent overfitting: L1/L2 weight penalty, dropout, early stopping, data augmentation, batch normalization.",
  "dateCreated": "2026-05-22T14:59:47.501Z",
  "dateModified": "2026-05-22T14:59:47.501Z",
  "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": []
}