xgboost regression hyperparameter optimization

hi dear form users

ı m new to knime platform. ı have a quaestions. ı want to predict by using xgboost

parameters={

"learning_rate":[0.1,0.01,0.001],
"n_estimators":range(100, 1200, 100),
}

xgbmodel = xg.XGBRegressor(randomstate=0)

this is my pyhton code and ı m searc by GridSearch to hyperparameter

. how can ı do this on knime ?