XGBoost is an open source machine learning library that implements optimized distributed gradient boosting algorithms. XGBoost uses parallel processing for fast performance, handles missing values well, performs well on small datasets, and prevents overfitting. All of these advantages make XGBoost a popular solution for regression problems such as forecasting.
Forecasting is a critical task for all kinds of business objectives, such as predictive analytics, predictive maintenance, product planning, budgeting, etc. Many forecasting or prediction problems involve time series data. That makes XGBoost an excellent companion for InfluxDB, the open source time series database.
