Classifying-Cardiovascular-disease-diagnosis-outcome-data-by-executing-a-deep-belief-network

Building a neural network to classify patients with cardiovascular diseases by executing a deep belief network

Architecture

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

Results