This course provides an overview of the Risk Modeling nodes in SAS Visual Data Mining and Machine Learning. It prepares members of your organization to develop scorecards. The course includes hands-on demonstrations and teaches you key concepts, terminology, and base functionality that are integral to visual risk modeling.
Ismerje meg hogyan...
use SAS Visual Data Mining and Machine Learning to:
- Add data to the pipeline.
- Insert an Interactive Grouping node into the pipeline and specify grouping options.
- Add a Scorecard node to generate a scorecard.
- Control the selection and optimization option of the logistic regression model.
- Manually adjust bins and scorecard cutoff values.
- Insert a Reject Inference node into the pipeline.
Kinek ajánljuk
Modelers, credit analysts, and others who are interested in risk modeling
Elérhető képzési formák | Időtartam | | |
e-Learning: |
8 óra/180 nap licensz |
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Before attending this course, you should have completed the Supervised Machine Learning Pipelines Using SAS Viya course. Other prerequisites are knowledge of and experience with logistic regression, which you can gain by completing the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression and Forecasting Using Model Studio in SAS Viya courses.
This course addresses SAS Risk Modeling Add-on for SAS Visual Data Mining and Machine Learning in SAS Viya 3.5. This course also touches on SAS Visual Analytics software.
