This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthor

Only authorized users are allowed to rename pages.

Only authorized users are allowed to delete pages.

Page revision history

Version Date Modified Size Author Changes ... Change note

Page References

Incoming links Outgoing links
Probabilistic Neural Network
Probabilistic Neural Network

Version management

Difference between version and

At line 1 added 28 lines
!!! Overview
[{$pagename}] ([PNN]) is a [Feedforward Neural network] which is widely used in [classification] and [pattern-recognition] problems.
[{$pagename}] use an [algorithm], the parent Probability density function (PDF) of each [Classification] is approximated by a Parzen window and a non-parametric [function]. Then, using PDF of each class, the class probability of a new input data is estimated and Bayes’ rule is then employed to allocate the class with highest posterior probability to new input data. By this method, the probability of mis-classification is minimized. This type of [Artificial Neural network] was derived from the Bayesian network and a statistical algorithm called Kernel Fisher discriminant analysis.
∫
[{$pagename}] organizes the operations into a multilayered [Feedforward Neural network] with four layers:
* [Input layer]
* [Hidden layer]
* [Summation layer]
* [Output layer]
!! Category
%%category [Artificial Intelligence]%%
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
----
* [#1] - [Probability_density_function|Wikipedia:Probability_density_function|target='_blank'] - based on information obtained 2017-12-28-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop