This library contains a collection of @grafana/scenes objects which can be added to your Scenes to run interactive, responsive machine learning algorithms directly in the browser.
@grafana/scenes-ml currently contains implementations of the following:
- forecasting (using the MSTL/ETS algorithms)
- outlier detection (using the median absolute difference or DBSCAN algorithms)
- changepoint detection (using either Bayesian Online Changepoint Detection or Autoregressive Gaussian Process Changepoint Detection)
Under the hood, the heavy lifting is largely powered by the augurs library, which runs inside WebAssembly.
See that library for more information on the underlying algorithms.
See the Getting Started guide for usage documentation.
To work on @grafana/scenes-ml, please follow the guides below.
- Run
YARN_IGNORE_PATH=1 yarn linkfrompackages/scenes-mldirectory. - Run
yarn devfrompackages/scenes-mldirectory. - Run
yarn link @grafana/scenes-mlfrom app plugin directory. - Start app plugin development server.
Alternatively, use the demo app included in this repository.