Body: <p>Consider an extremely complicated feed-forward neural network training example but with no need of computational efficiency or limiting of processing time. </p>
  
  <p>What is the maximum number of hidden neurons <strong><em>h</em></strong> that a hidden layer should possess to detect all unique features/ correlations between input data from the previous layer which has <strong><em>n</em></strong> nodes?</p>
  
  <p>In other words if we wanted to create a neural network with a large number of neurons in a hidden layer, what is the maximum neuron count possible that helps the network train (give <strong><em>n</em></strong> neurons are in the previous layer)?</p>
  
Tags: <neural-networks><neurons><feedforward-neural-networks><hyper-parameters>
Title: Maximum number of neurons in a layer given number of neurons in previous layer
UserDisplayName: Vikhyat Agarwal
ThreadText: # Maximum number of neurons in a layer given number of neurons in previous layer
  
  (Asked by: username_0 on 2018-12-09)
  
  Consider an extremely complicated feed-forward neural network training example but with no need of computational efficiency or limiting of processing time.
  
  What is the maximum number of hidden neurons ***h*** that a hidden layer should possess to detect all unique features/ correlations between input data from the previous layer which has ***n*** nodes?
  
  In other words if we wanted to create a neural network with a large number of neurons in a hidden layer, what is the maximum neuron count possible that helps the network train (give ***n*** neurons are in the previous layer)?
  
  **Tags:** neural-networks, neurons, feedforward-neural-networks, hyper-parameters
  
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  ## 0 answers
  
  