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feature-engineering-cookbook

피처 엔지니어링 기법 카탈로그: 수치형/범주형/시계열/텍스트 변환, 피처 선택, 피처 스토어 설계. '피처 엔지니어링', '특성 공학', '변수 변환', '인코딩', '스케일링', '피처 선택', '피처 스토어', '피처 중요도' 등 데이터 전처리 및 피처 설계 시 이 스킬을 사용한다. data-engineer의 피처 엔지니어링 역량을 강화한다. 단, 모델 설계나 학습 관리는 이 스킬의 범위가 아니다.

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# Feature Engineering Cookbook — 피처 엔지니어링 기법 카탈로그

데이터 타입별 변환 기법, 피처 선택 방법, 피처 스토어 설계 가이드.

## 수치형 변환

### 스케일링

| 방법 | 공식 | 적합 | 부적합 |
|------|------|------|--------|
| StandardScaler | (x - μ) / σ | 정규분포, SVM, 로지스틱 회귀 | 이상치 민감 |
| MinMaxScaler | (x - min) / (max - min) | [0,1] 필요, 신경망 | 이상치 민감 |
| RobustScaler | (x - Q2) / (Q3 - Q1) | 이상치 존재 | — |
| PowerTransformer | Box-Cox / Yeo-Johnson | 왜도 큰 분포 | 음수값(Box-Cox) |