In the second of three posts on using automated analysis with SAS Visual Analytics, we used the automated analysis object to get a better understanding of our variable of interest, X-Sell and Up-sell Flag, and how it is influenced by other variables in our dataset. In this third and final […]
How SAS Visual Analytics’ automated analysis takes customer care to the next level – Part 3 was published on SAS Users.
One of the big benefits of the SAS Viya platform is how approachable it is for programmers of other languages. You don’t have to learn SAS in order to become productive quickly. We’ve seen a lot of interest from people who code in Python, maybe because that language has become […]
The post Using Python to work with SAS Viya and CAS appeared first on The SAS Dummy.
Here is a macro to generate binary features (also called dummy coding) from a nominal variable (also called a categorical variable, such as eye color). The automation saves time and avoids mistakes when there are many possible values to a category or …
This R code fits an artificial neural network in R and generates Base SAS code, so new records can be scored entirely in Base SAS. This is intended to be a simple, elegant, fast solution. You don’t need SAS Enterprise Miner, IML, or any other spe…
This code creates a decision tree model in R using party::ctree() and prepares the model for export it from R to SAS, so SAS can score new records without invoking R. I use this method for several reasons. First, it’s convenient for my workflow t…