Predictive model variable management

• US 20050234698A1
• Filed: 04/16/2004
• Published: 10/20/2005
• Est. Priority Date: 04/16/2004
• Status: Active Grant

• Current Assignee: Longhorn Automotive Group LLC (Alpha Alpha Intellectual Partners LLC)
• Original Assignee: Fortelligent LLC
• Inventors: Pinto, Stephen K., Mansfield, Richard
• Granted Patent: US 7,499,897 B2
• Time in Patent Office: Days
• US Class Current: 703/22
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Models are generated using a variety of tools and features of a model generation platform. For example, in connection with a project in which a user generates a predictive model based on historical data about a system being modeled, the user is provided through a graphical user interface a structured sequence of model generation activities to be followed, the sequence including dimension reduction, model generation, model process validation, and model re-generation. A graphical user interface enables a user of a model generation tool to view and manage subgroups of variables associated with generation of a predictive model including original source variables and derived variables; variable response functions are displayed; variables are edited and transformed into new more predictive variables.

Claims

1. A machine-based method comprising

providing a graphical user interface that enables a user of a model generation tool to view and manage subgroups of variables associated with generation of a predictive model including source variables associated with attributes of the original data and derived variables subsequently modified from the source variables.

2. The method of claim 1 in which the derived variables include constructed variables, and transformed variables.

3. The method of claim 1 also including

enabling the user to move variables between subgroups using a pointer.

4. The method of claim 1 in which the user interface enables a user to view, with respect to a selected variable, its definition and its response distribution relative to an outcome variable.

5. The method of claim 1 in which only variables within one of the subgroups are used in the model that is generated.

6. The method of claim 1 in which the subgroup to which each variable belongs is stored persistently.

7. A machine-based method comprising

in connection with a project in which a user generates a predictive model based on historical data about a system being modeled, enabling the user through a graphical user interface to manage and view information about predictor variables associated with the data.

8. The method of claim 7 in which the information includes a status of a predictor variable.

9. The method of claim 7 in which the information includes a status of a class of non-predictor variables.

10. The method of claim 7 in which the user interface enables the user to point and click to cause display of information about the variable.

11. The method of claim 10 in which the information about the variable comprises at least one of:

a description, a definition, a history of transformations, a response graph, and a link to the graph.

12. The method of claim 11 in which invocation of the link to the graph causes display of the probability of an event as a function of the variable.

13. The method of claim 7 also including enabling the user to cause a variable to be transformed, and including the transformed version of the variable in the information about predictor variables.

14. The method of claim 7 in which the predictor variables are grouped in the user interface, and also including enabling the user to move one or more than one variable from one group to another.

15. The method of claim 7 in which the graphical user interface represents filtered views of a data dictionary of an entire set of variables of the model.

16. The method of claim 7 in which the user interface enables the user to point and click to cause display of decision partition trees of the collection of predictor variables.

17. The method of claim 7 in which the user interface enables the user to point and click to cause display of response distribution functions of the collection of predictor values.