Browse all content tagged with Gradient Boosting
Gradient Boosting is a powerful machine learning ensemble technique for regression and classification. It builds models sequentially, typically with decision trees, to optimize predictions, improve accuracy, and prevent overfitting. Widely used in data science competitions and business solutions.
LightGBM, or Light Gradient Boosting Machine, is an advanced gradient boosting framework developed by Microsoft. Designed for high-performance machine learning tasks such as classification, ranking, and regression, LightGBM excels at handling large datasets efficiently while consuming minimal memory and delivering high accuracy.
XGBoost stands for Extreme Gradient Boosting. It is an optimized distributed gradient boosting library designed for efficient and scalable training of machine learning models, known for its speed, performance, and robust regularization.
