Microsoft's open-source fast gradient boosting framework for large-scale tabular data modelling.
LightGBM is Microsoft's open-source gradient boosting framework, notable for fast training, relatively low memory use and suitability for large tabular datasets. It is commonly used for classification, regression, ranking and predictive analysis.
Use cases: gradient boosting, tabular modelling, big data modelling, classification and regression, machine learning
Note: When comparing with XGBoost, CatBoost and similar models, use consistent data splits and validation strategies.
