Gradient Boosting vs Random Forest

Gradient boosting is a machine learning ensemble technique sequentially building decision trees that each correct previous prediction errors, enabling cryptocurrency models to achieve high accuracy with modest computational overhead.

An ensemble machine learning algorithm that trains multiple decision trees independently and combines their predictions to improve accuracy and reduce overfitting in cryptocurrency trading models.