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Home Multivariate Data Modeling Classification and Discrimination KNN classification  
See also: Classification vs. Calibration, Discrimination and Classification, kMeans Clustering, Memory Based Learning  
KNN classification
KNearest Neighbor (KNN) classification is a very simple, yet powerful classification method. The key idea behind KNN classification is that similar observations belong to similar classes. Thus, one simply has to look for the class designators of a certain number of the nearest neighbors and weigh their class numbers to assign a class number to the unknown.
It can be shown that the performance of a KNN classifier is always at least half of the best possible classifier for a given problem. One of the major drawbacks of KNN classifiers is that the classifier needs all available data. This may lead to considerable overhead, if the training data set is large.


Home Multivariate Data Modeling Classification and Discrimination KNN classification 
Last Update: 20121008