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Which statement is TRUE about RBM?1 pointAt the hidden layer's nodes, X is multiplied by a W (weight matrix) and added to h_bias.Each node in the first layer has a bias.The RBM reconstructs data by making several forward and backward passes between the visible and hidden layers.It is a Boltzmann machine, but with no connections between nodes in the same layer.All of the above

Question

Which statement is TRUE about RBM?1 pointAt the hidden layer's nodes, X is multiplied by a W (weight matrix) and added to h_bias.Each node in the first layer has a bias.The RBM reconstructs data by making several forward and backward passes between the visible and hidden layers.It is a Boltzmann machine, but with no connections between nodes in the same layer.All of the above

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Solution

The statement that is TRUE about RBM (Restricted Boltzmann Machine) is: "It is a Boltzmann machine, but with no connections between nodes in the same layer."

This is because, by definition, a Restricted Boltzmann Machine is a type of Boltzmann machine with the restriction that there are no connections between nodes in the same layer. This restriction simplifies learning and allows for more efficient training algorithms.

The other statements are not entirely accurate:

  • At the hidden layer's nodes, X is not multiplied by a W (weight matrix) and added to h_bias. Instead, the input is multiplied by a weight matrix and then a bias is added, but this happens at the visible layer's nodes, not the hidden layer's nodes.
  • Not every node in the first layer has a bias. Only the visible layer nodes have a bias in an RBM.
  • The RBM does not reconstruct data by making several forward and backward passes between the visible and hidden layers. Instead, it uses a process called contrastive divergence, which involves a forward pass and a backward pass, but not several.

This problem has been solved

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what is the difference between Autoencoders and RBMs?1 pointAutoencoders have less layeres than RBMS.Autoencoders use a deterministic approach, but RBMs use a stochastic approach.Autoencoders are used for supervised learning, but RBMs are used for unsupervised learning.All of the above

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