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Additional
discriminant analysis
English Wikipedia - The Free Encyclopedia
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Linear discriminant analysis
Linear discriminant analysis
(
LDA
) is a generalization of
Fisher's linear discriminant
, a method used in
statistics
,
pattern recognition
and
machine learning
to find a
linear combination
of
features
that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a
linear classifier
, or, more commonly, for
dimensionality reduction
before later
classification
.
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