Intuitive Explanation of XGBoost

A simple explanation and implementation of the most popular machine learning algorithm

XGBoost is a machine-learning algorithm that can be compared to a guessing game, similar to guessing the number of candies in a jar. In this game, you are presented with a jar of candies and asked to estimate the number of candies inside the jar without actually counting them. You receive numerous hints and clues that aid you in making an improved guess, and after each guess, you receive feedback on how close or far your estimate is from the correct answer. As you continue to make guesses, you become more skilled at the game, ultimately leading to accurate estimates.

XGBoost stands for Extreme Gradient Boosting, a supervised machine-learning algorithm for regression and classification.

XGBoost is a powerful supervised machine-learning algorithm that uses decision trees employing a gradient-boosting feedback mechanism to iteratively improve its predictions, resulting in increased accuracy over time.

Decision tree

Decision tree is a popular machine-learning algorithm that uses a tree-like structure to visualize the decision-making process of a model.