LightGBM

LightGBM, or Light Gradient Boosting Machine, is a machine learning framework designed for fast and efficient processing of large datasets. It builds decision trees, which are models that make predictions based on a series of rules derived from data features. LightGBM stands out for its ability to handle large amounts of data quickly and efficiently. It also uses a technique called gradient boosting, which improves the model's accuracy by learning from errors in previous predictions. This makes it popular for tasks in finance, marketing, and many other fields where predicting outcomes is essential.