قارن الطرق

	تحليل التمييز	تحليل العناقيد
المجال	الإحصاء	الإحصاء
العائلة	Latent structure	Latent structure
سنة النشأة	1936	1939–1967
صاحب الطريقة	Ronald A. Fisher	Robert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-means
النوع	Supervised classification and dimension reduction	Unsupervised classification / grouping
المصدر التأسيسي	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.	Everitt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913
الأسماء البديلة	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis	clustering, unsupervised classification, data clustering, numerical taxonomy
ذات صلة	4	5
الملخص	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.	Cluster analysis is a family of unsupervised multivariate techniques that partition a set of objects or observations into internally homogeneous, mutually distinct groups — clusters — based on measured characteristics, without any prior knowledge of group membership. It is widely used in market segmentation, bioinformatics, psychology, and social science to reveal natural groupings in data.