title: impact of labels' distribution in deep learning for regression problem
body: <p>I am trying to train a CNN model for a regression problem, after that, I categorize predicted labels into 4 classes and check some accuracy metrics. In confusion matrix accuracy of class 2,3 are around 54% and accuracy of class 1,4 are more than 90%. labels are between 0-100 and classes are 1: 0-45,2: 45-60, 3:60-70, 4:70-100. I do not know where the problem comes from Is it because of the distribution of labels in the training set and what is the solution! Regards...
  I attached the plot in the following link.</p>
  
  <p><a href="https://i.stack.imgur.com/t5etp.png" rel="nofollow noreferrer">Training set target distribution</a></p>