DecisionTree vs RandomForest vs XGBoost

Hey, it’s me again, i have just now finished understanding the concepts of the decision tree and tree ensembles, which shocks me how i was using all of them without even understanding how they are worked. But now after i understand each of them, if i have no problem with the computation power, I think:

(a) I should choose the XGBoost rather than using the DecisionTree and RandomForest, because it perfomed better than both of them.

(b) It will be waste of time as i tried running the three of them together to see which one will achieve better, as i think it is guaranteed that XGBoost is better and achieve higher performance.

i would really appreciate confirming my understandings, or negotiate if i am misunderstanding some concept?

Yes, generally XGBoost performs better! I would suggest you to go to discussions like in Kaggle for competitions with structured data and see what modeling approaches are more popular.

Cheers,
Raymond

Thanks for your advice, i will check them out