The modeling nodes do not show the confusion matrix for the test data set. You will need to write your own SAS code in order to get this confusion matrix. If you add a SAS Code node after the modeling node, you can write the following code to get the confusion matrix:
***In this example, I am using the SAS Enterprise Miner macro variable of &em_import_test that will use the test data set. I am using the target variable named target. If my target variable is bad, then I use f_bad and I_bad;
proc freq data=&em_import_test;
tables f_target*I_target;
run;
The modeling nodes do not show the confusion matrix for the test data set. You will need to write your own SAS code in order to get this confusion matrix. If you add a SAS Code node after the modeling node, you can write the following code to get the confusion matrix:
***In this example, I am using the SAS Enterprise Miner macro variable of &em_import_test that will use the test data set. I am using the target variable named target. If my target variable is bad, then I use f_bad and I_bad;
proc freq data=&em_import_test;
tables f_target*I_target;
run;
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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.