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CIROH Dev Con SHAP Values Workshop

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Created:	May 15, 2025 at 2:22 p.m. (UTC)
Last updated:	May 27, 2025 at 3:47 p.m. (UTC)
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Abstract

This workshop introduces participants to SHAP (SHapley Additive exPlanations) values (Lundberg & Lee, 2017), a useful tool for interpreting machine learning models by analyzing feature importance. Participants will learn the fundamentals of SHAP values and their practical applications to understand how individual features influence predictions in regression and classification models. Using Python libraries, we will walk through hands-on examples to explore how SHAP values can enhance model transparency, provide actionable insights, and build trust in machine learning predictions, with a focus on real-world applications in water resources.

Learning Outcomes:

Understand SHAP values and their role in interpreting machine learning models.
How to implement SHAP values in Python
How to post-process SHAP tool output to create visualizations (e.g., bee swarm plot)
How qualitative evaluation of SHAP values can yield process insights for the system being modeled

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Spatial

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WGS 84 EPSG:4326

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Place/Area Name:

Continental United States

North Latitude

49.7245°

East Longitude

-66.2695°

South Latitude

24.6870°

West Longitude

-124.9805°

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How to Cite

Myers, H. (2025). CIROH Dev Con SHAP Values Workshop, HydroShare, http://www.hydroshare.org/resource/504107925379464dab88ff5780aefb5a

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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