Probabilistic Neural Network


Probabilistic Neural Network (PNN) is a Feedforward Neural network which is widely used in classification and pattern-recognition problems.

Probabilistic Neural Network 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.

Probabilistic Neural Network organizes the operations into a multilayered Feedforward Neural network with four layers:


Artificial Intelligence

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