title: Oversampling for Continuous Values
body: <p>I am trying to predict the processing time of a process by using xgboost regression algorithm in python. However I realised that my samples data is skewed to left and my algorithm struggles to predict longer process times (right side of histogram). I want to oversample the values I lack currently.</p>
  <p><img src="https://i.stack.imgur.com/jl45t.png" alt="Histogram of process times" /></p>
  <p>I have been looking at SMOTE algorithm for oversampling. All the examples I could find worked categorical y values. But my y values are continuous and I want to produce similarly continuous values. My current variables have continuous and binary values in them.</p>
  <p><img src="https://i.stack.imgur.com/uICDk.png" alt="Variables Data" /></p>
  <p><img src="https://i.stack.imgur.com/UJRaf.png" alt="Output Data" /></p>
  <p>Do you have any suggestions to oversample such data?
  Thanks</p>