feat: complete wikification of War Commander batch 1&2 and final grey dot cleanup

10_Wiki/Topics/AI/Boosting-Algorithms-XGBoost-LightGBM.md

@@ -1,6 +1,6 @@
 ---
 id: P-REINFORCE-AI-BOOSTING
-category: "[[10_Wiki/💡 Topics/AI]]"
+category: "10_Wiki/💡 Topics/AI"
 confidence_score: 1.0
 tags: [Boosting, XGBoost, LightGBM, Gradient Boosting, Machine Learning]
 last_reinforced: 2026-04-20
@@ -23,5 +23,5 @@ last_reinforced: 2026-04-20
 - 부스팅 모델은 강력하지만 과적합(Overfitting)에 취약하다. 이를 위해 학습률(Learning rate)을 낮추고, 나무의 깊이를 제한하며, 조기 종료(Early stopping) 전략을 반드시 사용해야 한다.
 
 ## 🔗 지식 연결 (Graph)
-- Related: [[Decision-Tree]] , [[Bias-Variance-Tradeoff]]
-- Tool: [[Data-Science-Toolkit]]
+- Related: Decision-Tree , [[Bias-Variance-Tradeoff]]
+- Tool: Data-Science-Toolkit