Open-source gradient boosting machine learning library for tabular data modelling and predictive analysis.
XGBoost is a high-performance open-source gradient boosting library widely used for tabular data modelling, classification, regression, ranking and forecasting. It suits research data prediction, feature importance analysis and baseline models for machine learning competitions.
Use cases: gradient boosting, tabular modelling, classification and regression, predictive analysis, machine learning
Note: Model performance depends on data quality, validation design and tuning — don't judge it by training-set results alone.
