Does XGBoost use an independent tree for each class in multi class problem?
user
yes, xgboost uses an independent tree for each class in a multi-class problem. in the case of multi-class classification, xgboost utilizes the "softmax" objective function for training and applies the "multi:softprob" objective for predicting probabilities.

for a problem with k classes, it constructs k trees (or k times the number of boosting rounds) where each tree is responsible for predicting the probability of a given instance belonging to that specific class. the final prediction for a given instance is the class with the highest probability.
assistant
Yes, XGBoost uses an independent tree for each class in a multi-class problem. In the case of multi-class classification, XGBoost utilizes the "softmax" objective function for training and applies the "multi:softprob" objective for predicting probabilities.

For a problem with k classes, it constructs k trees (or k times the number of boosting rounds) where each tree is responsible for predicting the probability of a given instance belonging to that specific class. The final prediction for a given instance is the class with the highest probability.
assistant