Webinar: Using Random Forest for Spatial Extrapolation of Streamflow Metrics
In this webinar, Environmental Modeler Jens Kiesel introduces the Random Forest machine learning algorithm for hydrological predictions. He shares machine learning techniques and discusses the pros and cons of the algorithm.
The webinar's core focuses are input data processing, applying the algorithm, assessing performance, and identifying the importance of the predictor variables targeted to streamflow simulations. We share insights into lessons learned and pitfalls to using Random Forest, and provide a simple code example to get you started implementing your own Random Forest machine learning model.
Available Resources
Presentation slides (PDF). Please click the link above.
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For Additional Information
Contact Dr. Jens Kiesel to learn more about our work with machine learning and suggest topics for future webinars.