For the latest version of JMP Help, visit JMP.com/help.

Predictive and Specialized Modeling > Predictor Screening > Overview of the Predictor Screening Platform
Publication date: 07/30/2020

Overview of the Predictor Screening Platform

Predictor screening is useful for the identification of significant predictors from a large number of candidates. Suppose you had hundreds of Xs and needed to determine which of those were most significant as predictors of an outcome.

The predictor screening platform uses a bootstrap forest to identify potential predictors of your response. For each response, a bootstrap forest model using 100 decision trees is built. The column contributions to the bootstrap forest model for each predictor are ranked. Because the bootstrap forest method involves a random component, column contributions can differ when you rerun the report. For more information about decision trees, see Partition Models.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).