MONITORING AND COMPARING FEATURES ACROSS ENVIRONMENTS
First Claim
Patent Images
1. A method, comprising:
- selecting, by one or more computer systems, a set of entity keys associated with reference feature values used with a machine learning model, wherein the reference feature values are generated in a first environment;
matching, by the one or more computer systems, the set of entity keys to feature values from a second environment;
comparing the feature values and the reference feature values to assess a consistency of a feature across the first and second environments; and
outputting a result of the assessed consistency for use in managing the feature in the first and second environments.
1 Assignment
0 Petitions
Accused Products
Abstract
The disclosed embodiments provide a system for processing data. During operation, the system selects a set of entity keys associated with reference feature values used with one or more machine learning models, wherein the reference feature values are generated in a first environment. Next, the system matches the set of entity keys to feature values from a second environment. The system then compares the feature values and the reference feature values to assess a consistency of a feature across the first and second environments. Finally, the system outputs a result of the assessed consistency for use in managing the feature in the first and second environments.
-
Citations
20 Claims
-
1. A method, comprising:
-
selecting, by one or more computer systems, a set of entity keys associated with reference feature values used with a machine learning model, wherein the reference feature values are generated in a first environment; matching, by the one or more computer systems, the set of entity keys to feature values from a second environment; comparing the feature values and the reference feature values to assess a consistency of a feature across the first and second environments; and outputting a result of the assessed consistency for use in managing the feature in the first and second environments. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
-
13. A system, comprising:
-
one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to; select a set of entity keys associated with reference feature values used with one or more machine learning models, wherein the reference feature values are generated in a first environment; match the set of entity keys to feature values from a second environment; compare the feature values and the reference feature values to assess a consistency of a feature across the first and second environments; and output a result of the assessed consistency for use in managing the feature in the first and second environments. - View Dependent Claims (14, 15, 16, 17, 18, 19)
-
-
20. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:
-
selecting a set of entity keys associated with reference feature values used with one or more machine learning models, wherein the reference feature values are generated in a first environment; matching the set of entity keys to feature values from a second environment; comparing the feature values and the reference feature values to assess a consistency of a feature across the first and second environments; and outputting a result of the assessed consistency for use in managing the feature in the first and second environments.
-
Specification