방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 로지스틱 회귀× | 다항 로지스틱 회귀× | |
|---|---|---|
| 분야≠ | 연구 통계 | 계량경제학 |
| 계열≠ | Process / pipeline | Regression model |
| 기원 연도≠ | 1958 | 1974 |
| 창시자≠ | David Roxbee Cox | McFadden |
| 유형≠ | Method | Multinomial logistic regression |
| 원전≠ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ | McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503 |
| 별칭≠ | logit model, binomial logistic regression, LR | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon |
| 관련≠ | 3 | 5 |
| 요약≠ | Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science. | Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category. |
| ScholarGate데이터셋 ↗ |
|
|