Building a neural network to classify patients with cardiovascular diseases by executing a deep belief network
A deep belief network lumps together manifold restricted Boltzmann machines(RBM) by permitting innumerable hidden layers, thus magnifying the complexity of a neural network.
Here, the figure outlines the structure of the Deep Belief Network(DBN) in such a way that the input layer holds 11 neurons with a relu activation, three hidden layers hold 11 neurons with a relu activation function, and the output layer generates labels with a sigmoid function
![dbn_architecture](https://private-user-images.githubusercontent.com/56320349/292645519-46b4bfe3-8187-426a-b529-f480438f2995.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.H507dhYgVrE7pWrUsOGgdsAxst5KwL-DpPYBawVbWpc)