What is Xgboost? How it is different from Random Forest?

Question

Accepted Answer

Xgboost is a gradient boosting algorithm used for classification and regression tasks. It is faster and more accurate than Random Forest.

Xgboost stands for Extreme Gradient Boosting
It is a type of gradient boosting algorithm that uses decision trees
It is faster and more accurate than Random Forest
Xgboost uses a more regularized model formalization to control overfitting
Random Forest builds multiple decision trees and combines them to get a more accurate prediction
Xgboost is widely used in Kaggle competitions and other machine learning applications

Accepted Answer

XGBoost is an implementation of Gradient Boosted Trees. This is a boosting method where each tree tries to learn from the misclassifications of the previous trees, in a series. Specially in GBDT, the trees are represented as functions and the trees are added in an additive manner where the nth function or tree tries to learn from the gradient of the loss function up to n-1 trees.

Random forest is a bagging method which builds an ensemble of trees in parallel, each with m features at a time

What is Xgboost? How it is different from Random Forest?

Top Standard Chartered Credit Risk Analyst interview questions & answers

Popular interview questions of Credit Risk Analyst

Top HR questions asked in Standard Chartered Credit Risk Analyst