# Specify the interactions for MARS® Regression

Predictive Analytics Module > MARS® Regression > Interaction
###### Note

Select the interactions to consider in the model. Partial dependence plots are not available for an analysis that considers interactions.

An interaction means that the effect of a predictor depends on the value of other predictors. For example, the rate at which grain dries in an oven depends on the time in the oven, but the effect of time depends on the temperature of the oven. The time and temperature variables interact.

The limitation of interactions still allows multiple basis functions for single variables. To force a continuous predictor to have only a linear effect, go to the Options for the analysis and disable transformations for the predictor.
• Do not allow any interactions (Additive model) : Do not allow predictor interactions. In this case, Minitab uses the additive model where the basis functions do not interact.
• Allow all interactions up to order: Order specifies the number of different predictors that can be in a basis function. For example, an order of 2 indicates that the effect of a predictor can depend on the value of 1 other predictor. An order of 3 indicates that the effect of a predictor can depend on the value of 2 other predictors. The following basis functions are an example of an interaction of order 3:
• BF1 = max(0, X1 − 800)
• BF2 = max(0, X2 − 50) * BF1
• BF3 = max(0, X3 − 10) * BF 2
An order of 4 indicates that the effect of a predictor can depend on the value of 3 other predictors.
• Select specific predictor interactions up to order: Order specifies the number of different predictors that can be in a basis function. For example, an order of 2 indicates the effect of a predictor can depend on the value of 1 other predictor. An order of 3 indicates that the effect of a predictor can depend on the value of 2 other predictors. An order of 4 indicates that the effect of a predictor can depend on the value of 3 other predictors. The following basis functions are an example of an interaction of order 3:
• BF1 = max(0, X1 − 800)
• BF2 = max(0, X2 − 50) * BF1
• BF3 = max(0, X3 − 10) * BF 2
• In Predictors, enter the columns that contain the predictors that you want to allow for the interactions. Enter at least as many predictors as the order of the interactions. For example, to consider interactions of order 2, enter 2 or more predictors. If you specify no predictors, then the analysis considers interactions among all of the predictors.