Description
Gradient-boosted decision tree models can be trained and used from Python workflows. XGBoost supports classification, regression, ranking, and high-performance machine-learning tasks across local and accelerated environments.
It is imported by notebooks, scripts, and ML services rather than opened as a standalone app. Model outputs depend on data quality and tuning, so validate results before using them for consequential decisions.