  We present a novel method for controlling extrapolation in the prediction
profiler in the JMP software. The prediction profiler is a graphical tool for
exploring high dimensional prediction surfaces for statistical and machine
learning models. The profiler contains interactive cross-sectional views, or
profile traces, of the prediction surface of a model. Our method helps users
avoid exploring predictions that should be considered extrapolation. It also
performs optimization over a constrained factor region that avoids
extrapolation using a genetic algorithm. In simulations and real world
examples, we demonstrate how optimal factor settings without constraint in the
profiler are frequently extrapolated, and how extrapolation control helps avoid
these solutions with invalid factor settings that may not be useful to the
user.
