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| 판별 분석× | 로지스틱 회귀× | |
|---|---|---|
| 분야≠ | 통계학 | 연구 통계 |
| 계열≠ | Latent structure | Process / pipeline |
| 기원 연도≠ | 1936 | 1958 |
| 창시자≠ | Ronald A. Fisher | David Roxbee Cox |
| 유형≠ | Supervised classification and dimension reduction | Method |
| 원전≠ | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ |
| 별칭≠ | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis | logit model, binomial logistic regression, LR |
| 관련≠ | 4 | 3 |
| 요약≠ | Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error. | 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. |
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