text: Title: Classification evaluation: Adjust confusion matrix and derivative metrics?
  Body: In utils_scoring.py, predicted values are calculated as a rounding of _probas_, hence can only be 0 or 1.
  
  When building the confusion matrix and calculating accuracy, these rounded _probas_ are compared with actual target values.
  
  If instead of 0/1 the input actuals are as in my example 1/2, the confusion matrix and accuracies are not correctly calculated.
  
  ![image](https://user-images.githubusercontent.com/10924953/30586708-c45b296c-9d28-11e7-8e72-d95fe2922838.png)
  