Body: <p>Say I have a batch of examples, each examples represent a state:</p>
  
  <pre><code>[0.1, 0.2, 0.5] #1st example
  [0.4, 0.0, 0.3] #2nd example 
  ..........
  [0.1, 0.1, 0.1] #16th example
  </code></pre>
  
  <p>I feed through the NN, and then the NN predict the following class:</p>
  
  <pre><code>[move up]   #1st example
  [move down] #2nd example
  ........
  [move left] #16th example
  </code></pre>
  
  <p>And then I take the square loss (which calculated to be 0.1 after taking average over 16 examples), and do backward propagation. </p>
  
  <p>So, can I assume that each of these examples will assign (or contribute) to a 0.1 loss?</p>
  
Tags: <training><backpropagation><objective-functions>
Title: Training by one batch of examples, what does it mean
UserDisplayName: Nygen Patricia
ThreadText: # Training by one batch of examples, what does it mean
  
  (Asked by: username_0 on 2018-11-22)
  
  Say I have a batch of examples, each examples represent a state:
  [0.1, 0.2, 0.5] #1st example
  [0.4, 0.0, 0.3] #2nd example 
  ..........
  [0.1, 0.1, 0.1] #16th example
  
  I feed through the NN, and then the NN predict the following class:
  [move up]   #1st example
  [move down] #2nd example
  ........
  [move left] #16th example
  
  And then I take the square loss (which calculated to be 0.1 after taking average over 16 examples), and do backward propagation. 
  So, can I assume that each of these examples will assign (or contribute) to a 0.1 loss?
  
  **Tags:** training, backpropagation, objective-functions
  
  ---
  
  ## 0 answers
  
  