Why is the decision forest better than the random forest?

Related questions

1. What is N_estimators in random forest?
2. Is Random Forest an ensemble method?
3. What is Nthread in XGBoost?
4. How does XGBoost algorithm work?
5. Is Random Forest good for regression?
6. Is XGBoost tree based?
7. What is the difference between GBM and XGBoost?
8. How does XGBoost work for classification?

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1. #reduce
2. #forest
3. #variance
4. #aggregated
5. #different
6. #results
7. #final
8. #forests
9. #increasing
10. #simply
11. #models
12. #collection
13. #powerful
14. #overfitting
15. #training
16. #result
17. #whose
18. #their
19. #decision
20. #error
21. #ability
22. #trees
23. #random
24. #substantially
25. #samples
26. #limit
27. #without