Jump to content

Classifier (mathematics): Difference between revisions

From Wikipedia, the free encyclopedia
Content deleted Content added
undoing information-destroying redirect: classifiers are a much more general topic that simple statistical classification
Line 1: Line 1:
In [[mathematics]], a '''classifier''' is a mapping from a (discrete or continuous) [[feature space]] ''X'' to a discrete set of labels ''Y''.
#REDIRECT [[Statistical classification]]

Classifiers may either be fixed classifiers or learning classifiers, and learning classifiers may in turn be divided into supervised and unsupervised learning classifiers.

There are a number of different types of classifier technologies:
* Bayes classifers:
** [[Naive Bayes classifier]]
** [[Optimal Bayes classifier]]
* [[Support vector machine]]s
* [[k-nearest neighbor]] classifiers
* [[neural network]] classifiers
* [[linear classifier]]s
** [[Fisher's linear discriminant]]
* [[quadratic classifier]]s

Classifiers are used in many practical applications, including [[optical character recognition]], [[speech recognition]] and [[handwriting recognition]], [[biometric identification]], [[document classification]] and Internet [[search engine]]s.

== See also ==
* [[Viterbi algorithm]]
* [[Dynamic time warping]]
* [[Machine learning]]

{{math-stub}}
[[Category:Pattern recognition]]
[[Category:Classification|*]]

Revision as of 09:25, 14 March 2005

In mathematics, a classifier is a mapping from a (discrete or continuous) feature space X to a discrete set of labels Y.

Classifiers may either be fixed classifiers or learning classifiers, and learning classifiers may in turn be divided into supervised and unsupervised learning classifiers.

There are a number of different types of classifier technologies:

Classifiers are used in many practical applications, including optical character recognition, speech recognition and handwriting recognition, biometric identification, document classification and Internet search engines.

See also