Antigravity Agent
36 lines
1.2 KiB
Markdown
36 lines
1.2 KiB
Markdown
---
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id: wiki-2026-0508-l2-regularization
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title: L2 Regularization
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category: 10_Wiki/Topics
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status: duplicate
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canonical_id: l1-and-l2-regularization
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duplicate_of: "[[L1-and-L2-Regularization]]"
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aliases: []
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source_trust_level: A
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confidence_score: 0.9
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verification_status: redirected
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tags: [duplicate, regularization, ridge, weight-decay]
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last_reinforced: 2026-05-10
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github_commit: pending
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---
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# L2 Regularization
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> **이 문서는 [[L1-and-L2-Regularization]] 의 중복본입니다.** Canonical 문서로 redirect.
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## 핵심 요약 (specialized aspects)
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- L2 = Ridge = weight decay. Penalty: $\lambda\|\beta\|_2^2$. 모든 계수를 0 근처로 수축하지만 정확히 0은 아님 — feature selection 효과 없음.
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- Closed-form: $\hat\beta = (X^TX + \lambda I)^{-1}X^Ty$.
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- Bayesian view: Gaussian prior on weights.
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- Deep learning에서 SGD weight_decay 파라미터로 자주 사용. AdamW (decoupled weight decay)가 표준.
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- L1과의 차이/조합 (Elastic Net)은 canonical [[L1-and-L2-Regularization]] 문서에 통합.
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## 🔗 Graph
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- 부모: [[L1-and-L2-Regularization]] (canonical)
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## 🕓 변경 이력
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | 중복 처리 — canonical 문서로 redirect |
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