Automatic Non-linear Regression

MARS® software is ideal for users who prefer results in a form similar to traditional regression while capturing essential nonlinearities and interactions. The MARS approach to regression modeling effectively uncovers important data patterns and relationships that are difficult, if not impossible, for other regression methods to reveal.

Features

  • Save MARS basis functions in Score Setup
  • MARS basis functions will be added during scoring to the output dataset
  • Ridge parameter in MARS
  • Automation: Build a series of models varying the maximum number of basis functions (Automate BASIS)
  • Automation: Varying the number of "folds" used in cross-validation (Automate CVFOLDS)
  • Automation: Repeat cross-validation process many times to explore the variance of estimates (Automate CVREPEATED)
  • Automation: Build a series of models using a user-supplied list of binning variables for cross-validation (Automate CVBIN)

  • Automation: Build a series of models varying the smoothness parameter (Automate MINSPAN)
  • Automation: Build a series of models varying the order of interactions (Automate INTERACTIONS)
  • Automation: Build a series of models varying the modeling speed (Automate SPEED)
  • Automation: Explore the impact of penalty on categorical predictors (Automate PENALTY=HLC)
  • Automation: Explore the impact of penalty on missing balues (Automate PENALTY=MISSING)
  • Automation: Build a series of models using varying degree of penalty on added variables (Automate PENALTY MARS)

    •