1. Machine Learning for SQL Use Cases
  2. Concepts
  3. Machine Learning Algorithms
  4. About Generalized Linear Model
  5. Scalable Feature Selection
  6. Feature Selection
  7. Configuring Feature Selection

Configuring Feature Selection

GLM configured for feature selection automatically determines the default behavior of the model.

Feature selection is a build setting for Generalized Linear Model models. It is not enabled by default. When configured for feature selection, the algorithm automatically determines appropriate default behavior, but the following configuration options are available:

  • The feature selection criteria can be AIC, SBIC, RIC, or α-investing. When the feature selection criteria is α-investing, feature acceptance can be either strict or relaxed.

  • The maximum number of features can be specified.

  • Features can be pruned in the final model. Pruning is based on t-statistics for linear regression or wald statistics for logistic regression.