What is the difference between RandomForestClassifier and XGBRFClassifier?
There is no detailed explanation about what XGBRFClassifier exactly is so I was wondering.
Data Science Stack Exchange is a question and answer site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field. It only takes a minute to sign up.
Sign up to join this communityThe primary difference between RandomForestClassifier and XGBRFClassifier is the package they are in. RandomForestClassifier is in the scikit-learn package and XGBRFClassifier is in the xgboost package. They are both are implementations of the Random Forest algorithm for classification.
XGBRFClassifier
andXGBRFRegressor
are SKL-like classes that provide random forest functionality. They are basically versions ofXGBClassifier
andXGBRegressor
that train random forest instead of gradient boosting, and have default values and meaning of some of the parameters adjusted accordingly." $\endgroup$Is it that XGBRFClassifier builds in parallel trees where at each tree the optimisation occurs with GB instead of information gain or gini and then aggregate these trees or it is something different?
based on what you quote (that's why I actually posted the question here haha) $\endgroup$