Wiki cleanup: error-doc removal, dedup merge, link normalization

10_Wiki/Topics 대규모 정리:
- 오류 캡처/미완성 stub 문서 227개 제거
- 교차폴더 중복 43클러스터 병합 (63파일 → redirect)
- 링크명 정규화: 깨진 링크 수정·redirect 직결·개념 매핑 ~2,400건
- 카테고리 MOC 6개 신규 생성
- Graph 섹션 미해결 related-keyword 링크 10,058건 제거

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

10_Wiki/Topics/AI_and_ML/Precision-Recall-Tradeoff.md

@@ -135,10 +135,9 @@ def tune_per_label(y_true, probs):  # (N, L)
 **기본값**: F1 maximize on validation set + calibration. Imbalanced면 PR-AUC report.
 
 ## 🔗 Graph
-- 부모: [[Classification]] · [[Evaluation_Metrics]]
-- 변형: [[F1_Score]] · [[F-beta_Score]] · [[PR_AUC]] · [[ROC_AUC]]
-- 응용: [[Imbalanced_Data]] · [[Anomaly_Detection]] · [[Object_Detection_mAP]] · [[Information_Retrieval]]
-- Adjacent: [[Confusion_Matrix]] · [[Threshold_Tuning]] · [[Calibration]] · [[Cost_Sensitive_Learning]]
+- 변형: [[ROC_AUC]]
+- 응용: [[Imbalanced_Data]] · [[Anomaly_Detection]] · [[Information Retrieval (IR)|Information_Retrieval]]
+- Adjacent: [[Threshold_Tuning]]
 
 ## 🤖 LLM 활용
 **언제**: classifier deployment threshold 결정, imbalanced eval report, cost-sensitive decision.