- #1
hisham.i
- 176
- 2
In neural network the learning algorithm ends when the mean squared error value is less than or equal to a value we have precised.
But i don't understand why we are comparing with the mean squared error and not the mean error?
What does the mean squared error represent?
But i don't understand why we are comparing with the mean squared error and not the mean error?
What does the mean squared error represent?