{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"F1 Score — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"<div style=\"font-family:sans-serif;border:1px solid #e0e0e0;border-radius:8px;padding:16px;max-width:600px;background:#ffffff;color:#111111;\"><p style=\"margin:0 0 4px;font-size:11px;color:#666;\">AI Glossary — gaks.ai</p><h3 style=\"margin:0 0 8px;font-size:16px;\">F1 Score (F1)</h3><p style=\"margin:0 0 12px;font-size:14px;line-height:1.6;\">The harmonic mean of precision and recall, providing a single metric that balances both. It is particularly useful when both false positives and false negatives matter, and when the dataset is imbalanced enough that overall accuracy would be misleading. A score of 1.0 is perfect; 0.0 is the worst possible.  See also: precision, recall, confusion matrix.</p><a href=\"https://gaks.ai/glossary/f1-score\" style=\"font-size:12px;color:#0077aa;\">Source: gaks.ai/glossary/f1-score →</a></div>"}