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Analisis Diskriminan Linear (LDA×Regresi Logistik×
BidangStatistikaStatistika Penelitian
KeluargaHypothesis testProcess / pipeline
Tahun asal19361958
PencetusRonald A. FisherDavid Roxbee Cox
TipeParametric linear classifier / dimensionality reductionMethod
Sumber perintisFisher, 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 ↗
AliasLDA, Fisher's LDA, Fisher's linear discriminant, discriminant function analysislogit model, binomial logistic regression, LR
Terkait73
RingkasanLinear Discriminant Analysis (LDA) is a parametric supervised classification method that finds the linear combination of continuous predictors that best separates two or more predefined groups. Introduced by Ronald A. Fisher in his landmark 1936 paper on taxonomic measurements, it simultaneously serves as a classifier and a dimensionality-reduction tool, and can be understood as the classification-oriented counterpart of MANOVA.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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ScholarGateBandingkan metode: Linear Discriminant Analysis (Classification) · Logistic Regression. Diakses 2026-06-17 dari https://scholargate.app/id/compare