PNN : Probabilistic Neural Network
Most algorithms are sequential, but PNN is a fully parallel processing algorithm. (20191031)
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is a probabilistic neural network?
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stochastic neural network is a type of neural network that includes probabilistic elements. That is, it can perform probabilistic operations when determining input-to-output mappings and produce probabilistic outputs.
Stochastic neural networks are commonly used in the field of deep learning and deep learning, and are particularly suited for tasks such as recognition and classification, image processing, and natural language processing. Stochastic neural networks can learn optimal parameters using algorithms such as stochastic gradient descent (SGD) and Monte Carlo methods.
Stochastic neural networks include multilayer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). For example, CNN is suitable for image processing tasks and RNN is suitable for natural language processing.
The advantage of probabilistic neural networks is that they can suppress overfitting and improve generalization ability. Additionally, even if the input is noisy, the effects of noise can be reduced by producing a probabilistic output. However, it may take a long time to train, so you may want a faster algorithm.