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Ordination or gradient analysis, in multivariate analysis, is a method complementary to data clustering, and used mainly in exploratory data analysis. Ordination orders objects that are characterized by values on multiple variables so that similar objects are near each other and dissimilar objects are farther from each other. Such relationships between the objects, on each of several axes , are then characterized numerically and/or graphically. Many ordination techniques exist, including principal components analysis , non-metric multidimensional scaling , correspondence analysis and its derivatives , canonical CA ], Bray–Curtis ordination, and redundancy analysis , among others. Contemporary developments for ordination focus on machine learning techniques or using statistical models instead.