MARS 2.0
Introduction
MARS is an innovative and flexible modeling tool that automates the building of accurate predictive models for continuous and binary dependent variables.
Multivariate Adaptive Regression Splines excels at finding optimal variable transformations and interactions, the complex data structure that often hides in high dimensional data. In doing so, this new generation approach to data mining uncovers business critical data patterns and relationships that are difficult, if not impossible, for other approaches to uncover.
Given a target variable and a set of candidate predictor variables, MARS automates all aspects of model development, including:
- Separating relevant from irrelevant predictors
- Transforming predictor variables exhibiting a nonlinear relationship with the target variable
- Determining interactions between predictor variables
- Handling missing values with new nested variable techniques
- Conducting extensive self tests to protect against overfitting
MARS enables analysts to rapidly search through all possible models and to quickly identify the optimal solution, providing insights that can lead to a definitive competitive advantage. And, because the software can be exploited via an easy to use GUI, intelligent default settings, and aesthetically appealing output, for the first time analysts at all levels can easily access MARS' innovations.
MARS for Windows also incorporates two alternative control modes that extend the program's features and capabilities. In addition to controlling MARS with the GUI, you can also issue commands at the command prompt or submit a command file.
MARS output is an easy to deploy regression model that can be automatically applied to new data from within MARS itself or exported as ready to run SAS and C source code. To facilitate interpretation of the model, the output also includes interpretive summary reports as well as exportable two- and three dimensional curve and surface plots.