Introduction
Models of data with a categorical response are called classifiers.
A classifier is built from training data, for which classifications
are known. The classifier assigns new test data to one of the categorical
levels of the response.
Parametric methods, like Discriminant Analysis, fit a parametric model to the training
data and interpolate to classify test data.
Nonparametric methods, like Classification Trees, use other means to determine classifications.
In this sense, classification methods are analogous to the methods
discussed in Nonlinear Regression.
 | Classification | | Discriminant Analysis |  |
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