Virtual fields allow you to create fields based on the ones that are available in the set of input fields known as data dictionary. Any virtual field becomes a part of the model that uses it.
In the Data analysis step, the values of virtual fields are calculated from the original field values and are subject to their own treatment (binning and grouping). This offers the ability to test different ways of treating the same data. Virtual fields are defined by using the virtual field screen.
A virtual field is an assignment in the form <variable> = <formula> . The virtual field screen hides the variable part of the equation, so that you can focus on the formula. The formula can continue over multiple lines, but a virtual field can contain only a single formula that uses fields and functions.
Types of virtual fields
Depending on the nature of the formula, a virtual field can be numeric or symbolic.
- Numeric formula
- Formed from the numeric fields and a large number of functions, such as logical and statistical functions.
- Symbolic formula
- Formed from the symbolic fields.
The type of virtual field used as the outcome in the Outcome definition screen automatically converts to the data type required by the type of model. Binary models and extended binary models require symbolic data type; continuous models require numeric data type.
- Adding virtual fields
Create fields based on the ones that are available in the set of input fields. Virtual fields offer the ability to test different ways of treating the same data.
- Modifying a virtual field
Modify the virtual field formula to test different ways of treating the same data.
- Deleting a virtual field
Delete a virtual field that you no longer need.
- Types of predictive models
Predictive models are optimized to predict different types of outcome.