P-ISSN: 2707-661X, E-ISSN: 2707-6628
Printed Journal | Refereed Journal | Peer Reviewed Journal
2022, Vol. 3, Issue 2, Part A
Artificial neural networks: Prediction for restricted Boltzmann machines
Author(s): Kama HN and Mankilik IM
Abstract: Artificial Neural Network (ANN) is the branch of Artificial Intelligence (AI) that is inspired by the architecture of the human brain. A type of recurrent ANN known as Restricted Boltzmann Machines (RBMs) are probabilistic graphical models that can be interpreted two-layered network of stochastic units with undirected connections between pairs of units in the two layers. RBMs are used specifically as a generative model. The result obtained from Neural Network Model shows 0.000373 errors with 88 steps. Prediction using neural network shows 0.9928202080, 0.3335543925 and 0.9775153014 while Converting probabilities into binary classes setting threshold level 0.5 result shows that the predicted results are 1, 0, and 1.
DOI: 10.33545/2707661X.2022.v3.i2a.50
Pages: 14-17 | Views: 431 | Downloads: 222
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How to cite this article:
Kama HN, Mankilik IM. Artificial neural networks: Prediction for restricted Boltzmann machines. Int J Commun Inf Technol 2022;3(2):14-17. DOI: 10.33545/2707661X.2022.v3.i2a.50
