So sánh phương pháp

	Phân tích nhân tố	K-Nearest Neighbors
Lĩnh vực	Thống kê nghiên cứu	Học máy
Họ	Process / pipeline	Machine learning
Năm ra đời	1931	1967
Người khởi xướng	Louis Leon Thurstone	Cover, T.M. & Hart, P.E.
Loại	Method	Instance-based (non-parametric) learning
Công trình gốc	Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press.	Cover, T.M. & Hart, P.E. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13(1), 21–27.
Tên gọi khác	EFA, CFA, latent variable modeling	KNN, K-En Yakın Komşu (KNN), nearest neighbor classifier, instance-based learning
Liên quan	3	5
Tóm tắt	Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data.	K-Nearest Neighbors (KNN), formalized by Cover and Hart in 1967, is a non-parametric, instance-based method that classifies or predicts a new observation by looking at the k closest examples in the training data. For classification it takes a majority vote among those neighbors; for regression it averages their values.