title: Azure-machine-learning: Compiling R-script, but different results
body: <p>I've built a ML model in Azure and most of my data transformation / feature generation steps have been carried out in R. 
  At first, I transformed the data in R itself (works faster) and uploaded the created csv to ML studio.</p>
  
  <p>Now that my model is finished I tried to run the R-code in ML studio itself, instead of manually uploading a transformed dataset. It runs flawlessly. However, when I compare the resulting datasets (the one uploaded and the one created) they differ. The columns have different means, formats and the model performs less. The actual data entries/cells look fine. </p>
  
  <p>I feel it has to do with the format of the columns so I tried stuff like converted the columns to character type, or converting the resulting dataset to csv (in ML studio) and letting ML studio figure out how to format them.</p>
  
  <p>So far, no results.</p>
  
  <p>Has anyone already faced this problem? What is the solution?</p>