Data with high dimensionality can include redundant and irrelevant variables. Sparseness and overfitting are common problems. Follow along with analytical training consultant Sharad Saxena in this SAS How To Tutorial and learn how you can use variable clustering to find the best inputs for models. What will you gain? Simpler models, shorter training times, and improved accuracy!
Chapters
00:00 – Introduction
01:58 – Simple correlational network example
03:24 – Precision matrix
04:33 – The variable clustering process
05:28 – Demonstration
19:23 – Summary
20:02 – Conclusion
Additional Resources
◉ AI and Machine Learning Courses – https://www.sas.com/en_us/training/pr...
◉ SAS Training | Advanced Machine Learning Using SAS Viya – https://learn.sas.com/course/view.php...
◉ SAS Help Center | The GVARCLUS Procedure – https://go.documentation.sas.com/doc/...
◉ SAS Communities | 4 Ways to Classify Feature Engineering in SAS Viya – https://communities.sas.com/t5/SAS-Co...
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