text: Title: Incorrect AUC value in CatBoost chart with sample_weight
  Body: I trained a dataset with sample weight using 3 algos: LightGBM, Xgboost, and CatBoost.
  I found that the learning curve chart for CatBoost doesn't take into account the sample weight but the score in the table does.
  Maybe you forgot to put sample_weight for CatBoost charts? I also see the problems in the ROC curve chart (but it's the same behavior among all models).
  Also, could this affect the training result e.g. terminating at the wrong place? Because I saw the model trained for many iterations.
  
  ![image](https://user-images.githubusercontent.com/15215732/167322423-1b70896b-890f-493e-ae7c-55bd1c7790c7.png)
  ![image](https://user-images.githubusercontent.com/15215732/167322603-542f692e-c088-4a4a-bd7b-f36720fb9d38.png)
  