Model tab (simulation)
For simulations based on a predictive model, the Model tab specifies the source of the model. For simulations that do not include a predictive model, the Model tab specifies the fields that are to be simulated.
Select an SPSS model file. This option specifies that the predictive model is defined in an IBM® SPSS® model file. An IBM SPSS model file is an XML file or a compressed file archive (.zip file) that contains model PMML created from IBM SPSS Statistics or IBM SPSS Modeler. Predictive models are created by procedures, such as Linear Regression and Decision Trees within IBM SPSS Statistics, and can be exported to a model file. You can use a different model file by clicking Browse and navigating to the file you want.
PMML models supported by Simulation
- Linear Regression
- Automatic Linear Model
- Generalized Linear Model
- Generalized Linear Mixed Model
- General Linear Model
- Binary Logistic Regression
- Multinomial Logistic Regression
- Ordinal Multnomial Regression
- Cox Regression
- Tree
- Boosted Tree (C5)
- Discriminant
- Two-step Cluster
- K-Means Cluster
- Neural Net
- Ruleset (Decision List)
- PMML models that have multiple target fields (variables) or splits are not supported for use in Simulation.
- Values of string inputs to binary logistic regression models are limited to 8 bytes in the model. If you are fitting such string inputs to the active dataset, make sure that the values in the data do not exceed 8 bytes in length. Data values that exceed 8 bytes are excluded from the associated categorical distribution for the input, and are displayed as unmatched in the Unmatched Categories output table.
Type in the equations for the model. This option specifies that the predictive model consists of one or more custom equations to be created by you. Create equations by clicking New Equation. This opens the Equation Editor. You can modify existing equations, copy them to use as templates for new equations, reorder them and delete them.
- The Simulation Builder does not support systems of simultaneous equations or equations that are non-linear in the target variable.
- Custom equations are evaluated in the order in which they are
specified. If the equation for a given target depends on another target,
then the other target must be defined by a preceding equation.
For example, given the set of three equations below, the equation for profit depends on the values of revenue and expenses, so the equations for revenue and expenses must precede the equation for profit.
revenue = price*volume
expenses = fixed + volume*(unit_cost_materials + unit_cost_labor)
profit = revenue - expenses
Create simulated data without a model. Select this option to simulate data without a predictive model. Specify the fields that are to be simulated by selecting fields from the active dataset or by clicking New to define new fields.