विधियों की तुलना करें

	कारक विश्लेषण	के-निकटतम पड़ोसी (K-Nearest Neighbors)
क्षेत्र	अनुसंधान सांख्यिकी	मशीन अधिगम
परिवार	Process / pipeline	Machine learning
उद्भव वर्ष	1931	1967
प्रवर्तक	Louis Leon Thurstone	Cover, T.M. & Hart, P.E.
प्रकार	Method	Instance-based (non-parametric) learning
मौलिक स्रोत	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.
उपनाम	EFA, CFA, latent variable modeling	KNN, K-En Yakın Komşu (KNN), nearest neighbor classifier, instance-based learning
संबंधित	3	5
सारांश	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.