VorhersageTools

VorhersageTools is an open-source software framework for forecasting and predictive analytics. It provides a modular toolkit for building, evaluating, and deploying predictive models primarily for time-series data, though it also supports cross-sectional data.

The project emerged in the mid-2010s in German-speaking research and industry circles as a community-driven alternative to proprietary forecasting software. It emphasizes reproducibility, transparency, and interoperability with common data science ecosystems.

Core components include data ingestion and preprocessing, feature engineering, a modeling engine with traditional statistical methods (ARIMA, exponential smoothing) and machine learning approaches, probabilistic forecasting and uncertainty quantification, model selection, cross-validation, and performance dashboards. Interfaces exist via Python, R, and optional integrations with data pipelines. It supports export of forecasts in standard formats and modular extension via plug-ins.

The system uses a modular architecture with a data layer, modeling layer, and deployment layer. Users can compose pipelines, compare models with standardized metrics (MAE, RMSE, Pinball loss for probabilistic forecasts), and deploy forecasts to dashboards or scheduling systems.

Used in academia and industry, including finance, energy, and meteorology, for forecasting demand, prices, weather indicators, and sensor measurements. The project maintains documentation and examples; development is community-driven with contributions via issue trackers and pull requests.

See also and related topics include time-series analysis, forecasting, Prophet, statsmodels, scikit-learn, and other open-source data science tools.