I have trained an XGBoost model using caret and now, I am calculating the mean SHAP value of each predictor using the package SHAPforxgboost, using the following code:

library(SHAPforxgboost)
to_select <- names(caret.xgb$trainingData)[-1] #variables to select in the training set, 
#the first one is the outcome, needs to be removed

shap_values <- shap.values(xgb_model = caret.xgb$finalModel,
                            X_train =data_train %>%
                              select(all_of(to_select))  %>% as.matrix()
                            
)
shap_long <- shap.prep(shap_contrib = shap_values$shap_score,
                       X_train = data_train %>%
                              select(all_of(to_select)) %>% as.matrix()
)

However, I get the following error:

Error in predict.xgb.Booster(xgb_model, (X_train), predcontrib = TRUE) : 
  Feature names stored in `object` and `newdata` are different!

But I am already selecting the same features as in the training set of the model, and when I use the function identical the output is TRUE.

Thank you!

I tried selecting the same features as in the training set in the model, in case the order of the variables was different, but the error is still the same. I also looked at the intersection of colnames() of each dataset, and it was complete.