text: Title: m2cgen output for xgboost with binary:logistic objective returns raw (not transformed) scores
  Body: Our xgboost models use the `binary:logistic'` objective function, however the m2cgen converted version of the models return raw scores instead of the transformed scores. 
  
  This is fine as long as the user knows this is happening! I didn't, so it took a while to figure out what was going on. I'm wondering if perhaps a useful warning could be raised for users to alert them of this issue? A warning could include a note that they can transform these scores back to the expected probabilities [0, 1] by `prob = logistic.cdf(score - base_score)` where `base_score` is an attribute of the xgboost model. 
  
  In our case, I'd like to minimize unnecessary processing on the device, so I am actually happy with the current m2cgen output and will instead inverse transform our threshold when evaluating the model output from the transpiled model...but it did take me a bit before I figured out what was going on, which is why I'm suggesting that a user friendly message might be raised when an unsupported objective function is encountered. 
  
  Thanks for creating & sharing this great tool!