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Explanatory Machine Learning Model Plots for Epidemiological and Real-World Evidence Studies

Started ‎07-17-2020 by
Modified ‎07-17-2020 by
Views 1,956

In this 26-minute video, you’ll hear about a standardized interpretability plots framework for evaluating and explaining patient-level machine learning models using observational health-care data. Presenter David Olaleye, Senior Manager HLS R&D, SAS, shows you how to use SAS® Cloud Analytic Services (CAS) action sets and model-agnostic interpretability tools available in SAS® Visual Data Mining and Machine Learning to explain the functional relationship between model features and target outcome variable.

 

 

Video Highlights

1:06 – Introduction

2:24 – Machine Learning Models

3:35 – Model Interpretability Tools

7:51 – Post-Predictive Model Features + Use Case

24:40 – Conclusion

 

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Related Resources

Interpreting Machine Learning Models in SAS (video tutorial)

SAS Visual Data Mining and Machine Learning (product page)

SAS Visual Data Mining and Machine Learning in SAS Viya: Interactive Machine Learning (training course)

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Last update:
‎07-17-2020 02:08 PM
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