I am build a linear regression model and a decision tree model using sklearn. I want to compare the performance of these two models, I have calculated the r2_score for both the models. I have calculated the model.score for both the values. I am confused which is a better metric to compare the performance of these models. Also what does model.score gives?
from sklearn.metrics import r2_score score_DT = r2_score(y_pred_DT,y_test) dt_score = regressorDT.score(X_test,y_test)