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Specify the default settings for MARS® Regression

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File > Options > Predictive Analytics > MARS® Regression

Specify the default methods for MARS® Regression. The changes you make to the defaults remain until you change them again, even after you exit Minitab Statistical Software.

Criterion for selecting optimal model
Choose between the following criteria to select the optimal number of basis functions for the model. This selection does not affect the search for the basis functions. If the 2 criteria select the same number of basis functions, then the models from the 2 criteria are the same.
  • R-squared: Select this option to display results for the model with the maximum R-squared value.
  • Mean absolute deviation: Select this option to display results for the model with the least mean absolute deviation.
Predictor 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.
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. 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
If you allow no interactions, the model uses the additive model. Predictors do not interact in the additive model.
Maximum number of basis functions
The default value of 30 works well in most cases. Consider a larger value when 30 basis functions seems too small for the data. For example, consider a larger value when you believe that more than 30 predictors are important.
If you are uncertain whether 30 is enough, review the initial results. For example, a larger value is more likely to improve the fit of the model if the R-squared value trends upwards as the analysis adds basis functions.
Minimum number of observations between knots
Allow MARS® to choose
The analysis uses sample size and model complexity to automatically select a value. The automatic value works well in most cases.
User specified
A value of 1 indicates that consecutive data points are eligible to be points where the basis function changes. The value of 1 allows the most rapid changes in the model predictions. Use larger values to create smoother models to explore more general relationships. Such smoother models are sometimes less accurate over certain ranges of the data.
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