Question

Which boosting algorithm has the advantage of parallel computation, efficient missing value treatment, and cache optimization features in its implementation?

a. AdaBoost
b. Gradient Boosting
c. XGBoost
d. Random Forest

Answer 1

XGBoost is the boosting algorithm that has the advantage of parallel computation, efficient missing value treatment, and cache optimization features in its implementation.

Step-by-step explanation:

The boosting algorithm that has the advantage of parallel computation, efficient missing value treatment, and cache optimization features in its implementation is XGBoost. XGBoost stands for eXtreme Gradient Boosting and is a popular machine learning algorithm that is widely used in various domains for its powerful and efficient features.

It is designed to be highly scalable and can utilize parallel computing to speed up the training process. XGBoost also has built-in methods to handle missing values and optimize cache usage, which further enhances its performance.

For example, XGBoost uses a technique called 'approximate tree learning' to handle missing values by assigning them to the direction that gives the maximum gain in the training objective. This allows XGBoost to handle missing values without the need for imputation or discarding data.