This example uses the Boston data table. Suppose you want to create a model to predict the median home value as a function of several demographic characteristics. Follow the steps below to build the neural network model:
Launch the Neural platform by selecting Analyze > Predictive Modeling > Neural.
Assign mvalue to the Y, Response role.
Assign the other columns (crim through lstat) to the X, Factor role.
Enter 0.2 for the Holdback Proportion.
Check the Transform Covariates option.
Neural Report
Actual by Predicted Plot
To get a general understanding of how the X variables are impacting the predicted values, select Profiler from the Model red-triangle menu. The profiler is shown in Profiler.
Some of the variables have profiles with positive slopes, and some negative. For example, rooms has a positive slope. This indicates that the more rooms a home has, the higher the predicted median value. The variable pt is the pupil teacher ratio by town. This variable has a negative slope, indicating that the higher the pupil to teacher ratio, the lower the median value.

Help created on 9/19/2017