What function takes the maximum of the prediction estimate from different models as the prediction in the Ensemble tool?

In the context of the Ensemble tool within SAS Enterprise Miner, the function that takes the maximum of the prediction estimates from different models is indeed the maximum function. This technique is commonly used in ensemble modeling to optimize the predictive performance by selecting the highest predicted value among various model outputs.

Using the maximum function allows you to capitalize on the strengths of different models, especially when they may each excel under various conditions or within specific subsets of the data. By choosing the highest prediction, the ensemble aims to provide a more robust and accurate overall prediction, particularly useful in scenarios such as binary classification where the highest confidence estimate might be desired.

In contrast, the average function would provide a mean of the predictions, which could dilute strong predictions by less confident ones. The minimum function would select the least confident estimate, which often isn’t beneficial for improving accuracy. Similarly, the range function, which is focused on the spread between maximum and minimum values, does not serve the purpose of selecting a single predictive output from the models. Thus, the maximum function is uniquely suited for this task in the ensemble context.