เปรียบเทียบวิธี

	Support Vector Machine	การถดถอยโลจิสติก
สาขาวิชา	การเรียนรู้ของเครื่อง	สถิติการวิจัย
ตระกูล	Machine learning	Process / pipeline
ปีกำเนิด	1995	1958
ผู้ริเริ่ม	Cortes, C. & Vapnik, V.	David Roxbee Cox
ประเภท	Maximum-margin classifier (kernel method)	Method
แหล่งต้นตำรับ	Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
ชื่อเรียกอื่น	Destek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier	logit model, binomial logistic regression, LR
ที่เกี่ยวข้อง	5	3
สรุป	The Support Vector Machine, introduced by Corinna Cortes and Vladimir Vapnik in 1995, is a classifier that finds the optimal separating hyperplane between classes in a high-dimensional space. It chooses the boundary that leaves the widest possible margin to the nearest training points, which makes its decisions robust on new data.	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.