Overview (LINEAR command)

Linear models predict a continuous target based on linear relationships between the target and one or more predictors.

Linear models are relatively simple and give an easily interpreted mathematical formula for scoring. The properties of these models are well understood and are typically very fast to train.

Options

Ensemble models. In addition to creating a "standard" linear model, you can use ensembles to improve model accuracy (boosting), improve model stability (bagging), or create a model for very large datasets.

Model selection. All fields can be entered into the model together, or forward stepwise or best subsets model selection can be used to choose the best fields.

Output. The procedure produces a model viewer object containing tables and charts for assessing the quality of the model; also you can save predicted values to the active dataset and the model to a file in PMML format.

Basic Specification

The basic specification is the LINEAR command and FIELDS subcommand with TARGET and INPUTS keywords. There must be a single continuous target and at least one input.

Note: Measurement level can affect the results. If any variables (fields) have an unknown measurement level, a data pass is performed to determine the measurement level before the analysis begins. For information on the determination criteria, see SET SCALEMIN.

Syntax Rules

  • All subcommands are optional.
  • Subcommands may be specified in any order.
  • Only a single instance of each subcommand is allowed.
  • An error occurs if a keyword is specified more than once within a subcommand.
  • Parentheses, equals signs, and slashes shown in the syntax chart are required.
  • The command name, subcommand names, and keywords must be spelled in full.
  • Empty subcommands are not allowed.
  • Any split field defined on the SPLIT FILE command cannot be used on this command.
  • Any field specifed on the WEIGHT command cannot be used on this command.

Limitations

  • If a categorical field has more than 1000 categories, the procedure does not run and no model is built.