I tried using a variable clustering node and a variable selection node to reduce the redundant variables, however, noticed that in the model comparison node, the random model scored best. why?
Insufficient detail.
Define the criteria used to determine best, share the data and show the code used (or generated by nodes) to make the models.
Then someone may be able to answer.
As mentioned, we need more details to help answer this question. As a best practice, I want to point you to a paper that hits on several data mining topics. It is several years old, but it is a fantastic paper to help in optimizing your data mining analysis. It is called Identifying and Overcoming Common Data Mining Mistakes. It is found at the following URL:
https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/073-2007.pdf
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Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.