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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 2,132

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

 

Read the Paper

 

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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