What do Model Comparison tools provide a tally of?

Model Comparison tools are designed to evaluate the performance of different predictive models by providing a tally of their accuracy or misclassification rates. These tools help practitioners in selecting the most effective model by comparing how well each model predicts outcomes based on a holdout sample or cross-validation.

By focusing on accuracy or misclassification, Model Comparison tools guide users in understanding how well their models are likely to perform on unseen data. Accuracy represents the proportion of correctly predicted instances in a dataset, while misclassification refers to instances where the model's predictions do not match the actual outcomes. This information is crucial for deciding which model not only performs well on training data but also generalizes effectively to new scenarios.

Other considerations, such as profit or loss, risk assessments, and model complexity, although important in the broader context of model evaluation, do not encapsulate the primary function of Model Comparison tools in SAS Enterprise Miner, which is fundamentally centered on assessing prediction accuracy.