XGBoost

XGBoost, short for Extreme Gradient Boosting, is a powerful machine learning algorithm used for making predictions. It works by combining many simple models, called decision trees, to create a strong overall model. Each tree focuses on correcting the errors of the previous ones, improving accuracy step by step. It’s popular for its speed and performance, especially in data competitions and real-world applications, due to its efficiency in handling large datasets and avoiding overfitting. Essentially, XGBoost helps computers make informed decisions by learning from examples and refining predictions through an iterative process.