Value over replacement feature (vorf) based determination of feature importance in machine learning
AssigneeIntuit Inc.
InventorsYehezkel Shraga Resheff, Talia Tron, Tzvi Itzhak Barnholtz
Life of this patent
Estimating the term…
Abstract
Systems and models are disclosed for determining a value over replacement feature (VORF) for one or more features of a machine learning model. An example method includes selecting one or more features used in the machine learning model, determining a comparison set of unused features not used in the machine learning model, for each unused feature in the comparison set, determining a difference in a specified metric when the selected one or more features are replaced by a corresponding unused feature from the comparison set, and determining the VORF to be the smallest difference in the specified metric.
Claims20
A method for determining a value over replacement feature (VORF) for one or more features of a machine learning model, the method comprising:
- selecting one or more features used in the machine learning model;
- determining a comparison set of unused features not used in the machine learning model;
- for each unused feature in the comparison set, determining a difference in a specified metric when the selected one or more features are replaced by a corresponding unused feature from the comparison set;
- and
- determining the VORF to be the smallest difference in the specified metric.
An apparatus coupled to a machine learning model, the apparatus comprising:
- one or more processors;
- and
- a memory storing instructions, wherein execution of the instructions by the one or more processors, causes the apparatus to perform operations comprising:
- selecting one or more features used in the machine learning model;
- determining a comparison set of unused features not used in the machine learning model;
- for each unused feature in the comparison set, determining a difference in a specified metric when the selected one or more features are replaced by a corresponding unused feature from the comparison set;
- and
- determining a value over replacement feature (VORF) to be the smallest difference in the specified metric.
A non-transitory computer-readable storage medium storing instructions which, when executed by one or more processors of an apparatus coupled to a machine learning model, cause the apparatus to perform operations comprising:
- selecting one or more features used in the machine learning model;
- determining a comparison set of unused features not used in the machine learning model;
- for each unused feature in the comparison set, determining a difference in a specified metric when the selected one or more features are replaced by a corresponding unused feature from the comparison set;
- and
- determining a value over replacement feature (VORF) to be the smallest difference in the specified metric.
Dependencies are inferred from the claim text.