SAS Model Studio's Model Comparison view displays results for logistic regression, gradient boosting, and random forest models after an AutoML pipeline run. Which metric does SAS Model Studio use by default to rank classification models in this comparison?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because SAS Model Studio defaults to validation-set misclassification rate as the primary ranking metric for classification pipelines in the model comparison view. A is wrong; training metrics would favor overfitting models.
Full explanation below image
Full Explanation
B is correct because SAS Model Studio defaults to validation-set misclassification rate as the primary ranking metric for classification pipelines in the model comparison view. A is wrong; training metrics would favor overfitting models. C is wrong; KS on training data is also biased. D is wrong; the test set is held out and not used for comparison/ranking.