2.4 Model Selection Classes
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. These classes are contained in Table 3.
Table 3: The Model Selection Classes
| Class Name | Description |
Describes confidence intervals for regression predictions and parameter estimates. | |
Encapsulates four different model selection algorithms for linear regression. The algorithms are forward, backward, stepwise, and exhaustive selection. | |
The class for logistic regression model selection. Provided with a logistic regression model containing a set of candidate predictor variables. |
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