Methods and formulas for the model summary in MARS^® Regression

Note

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Select the method or formula of your choice.

In This Topic

Important predictors
R-squared
Root mean squared error (RMSE)
Mean squared error (MSE)
Mean absolute deviation (MAD)
Mean absolute percent error (MAPE)
Notation

Important predictors

The number of predictors with positive relative importance.

A MARS^® Regression model comes from a sequence of basis functions that improve the model. The importance scores come from the optimal model that the analysis identifies. To calculate the importance score, the analysis finds the change in the mean squared error when all basis functions for a predictor are removed from the optimal model and the reduced model is refit to the training data. The relative importance compares the importance score for a predictor to the maximum importance score.