What inspired this wish list request? JMP is a great tool for data exploration, and helps build quickly prototypes for predictive models, to see if there is an added value in pushing the analysis and modeling further.
Looking at the panel "Overall Statistics" for a classification topic, I find there may be some performance metrics missing that are frequently used in the Machine Learning / Data Science world.
Here are the metrics currently displayed for a classification topic (example from a bootstrap forest):
What is the improvement you would like to see? I would like to see displayed commonly used performance metrics for classification, such as Sensivity, Specificity, Precision, Accuracy, F1 score, Matthews Correlation Coefficient ...
Perhaps directly under the Confusion matrix ?
Here are the possible metrics in use for classification topics from an online calculator, with the formulas explained : Confusion Matrix - Online Calculator (onlineconfusionmatrix.com)
Why is this idea important? As JMP is trying to bridge the gap between the Statistics and Machine Learning worlds by integrating several models from these two modeling mindsets in one platform, it would make sense to also integrate Machine Learning performance metrics in the results of a classification model, in order to have all infos in the same place and be able to speak the same common language.