<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>

<training><backpropagation><objective-functions>
Training by one batch of examples, what does it mean
Nygen Patricia
# 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


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## 0 answers

