Model Selection

Module Description

Model Selection Classes take a regression object from which they extract the regression data and calculation object. They search subsets of the predictors and select an optimal subset by applying a user-defined model evaluation function.

Classes
class	RWInterval< T >
	A class template for describing an interval of values. More...
class	RWLinRegModelSelector< F >
	Encapsulates four different model selection algorithms for linear regression: forward, backward, stepwise, and exhaustive. More...
class	RWLogRegModelSelector< F >
	For a logistic regression model, selects a subset of predictor variables that accounts for the variation in the regression model's observation variable. More...
class	RWRegressionModelSelector< T, S, F >
	The base class for the model selection classes for linear or logistic regression. More...

Enumerations
enum	RWSearchMethod { rwForwardSelection, rwBackwardSelection, rwStepwiseSelection, rwExhaustiveSelection }

Enumeration Type Documentation

enum RWSearchMethod

Designates the search method.

Enumerator
rwForwardSelection
rwBackwardSelection
rwStepwiseSelection
rwExhaustiveSelection