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An introduction to tree models (decision trees and random forest) for regression. This tutorial starts from the very basics.

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Tree Models for Regression

This repository consists of a tutorial on an introduction to Tree models for Regression. I presented this at the GeoSMART Hackweek at the eScience Institute of the University of Washington, Seattle. The tutorial is deployed on GeoSMART Website. Learn more about GeoSMART on their GitHub repository and their website.

Acknowledgements

  • Many thanks to the eScience Institute and all organizing members for allowing me to deploy/present this tutorial and for supporting my travel to Seattle.
  • Many thanks to Prof. Marshall of the Department of Geoscience at Boise State University (my advisor) for allowing me to present this tutorial, guiding me through its compilation, and also supporting my travel.
  • Many thanks to Prof. Mead of the Department of Mathematics at Boise State University for her comments and for helping re-arrange the contents of this tutorial.

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An introduction to tree models (decision trees and random forest) for regression. This tutorial starts from the very basics.

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