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US 12,547,645 B2Granted
Systems and methods for classification of database records by mitigating bias using random data re-censoring
AssigneeCapital One Services, LLC
InventorsWendi Liu, Xue Li, Fei Tong, Bing Liu
Life of this patent
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Abstract
Methods and systems are described herein for improving data processing efficiency of classifying user files in a database. More particularly, methods and systems are described herein for improving data processing efficiency of classifying user files in a database in which the user files have a temporal element. The methods and systems described herein accomplish these improvements by mitigating bias using random data censoring.
Claims16
A system for classifying user files in a database into disparate states by mitigating bias using random data censoring, the system comprising:
- one or more processors;
- and
- a non-transitory, computer-readable medium comprising instructions that when executed by the one or more processors cause operations comprising:
- receiving a request to determine respective probabilities that a user record for a user belongs to each of a plurality of user record states;
- retrieving a user record history for the user record, wherein the user record history comprises periodic status checks, wherein each of the periodic status checks comprises a status check date;
- determining that the user record history comprises a bias associated with the periodic status checks;
- in response to determining that the user record history comprises a bias, generating a re-censored record history by randomly re-censoring the user record history based on a set build date, wherein generating the re-censored record history by re-censoring the user record history based on the set build date comprises:
- determining the set build date based on an availability of data in the user record history;
- determining a respective periodic status check proximity at each of the periodic status checks by:
- retrieving a time stamp for each periodic status check of the periodic status checks;
- and
- comparing the time stamp to the set build date;
- determining a respective re-censoring probability at each of the periodic status checks based on the respective periodic status check proximity;
- and
- determining whether a respective user record status at each of the periodic status checks is available based on the respective periodic status check proximity;
- generating a feature input for the user record history based on the respective user record status at each of the periodic status checks that is available in the re-censored record history;
- processing the feature input using a first model;
- receiving a first output of the first model indicating the respective probabilities that the user record for the user belongs to each of the plurality of user record states;
- and
- generating a recommendation based on the first output.
17 more elements
A method of classifying user files in a database into disparate states by mitigating bias using random data censoring, the method comprising:
- receiving a request to determine respective probabilities that a user record for a user belongs to each of a plurality of user record states;
- retrieving a user record history for the user record, wherein the user record history comprises periodic status checks, wherein each of the periodic status checks comprises a status check date;
- determining that the user record history comprises a bias associated with the periodic status checks;
- in response to determining that the user record history comprises a bias, generating a re-censored record history by randomly re-censoring the user record history based on a set build date, wherein generating the re-censored record history by re-censoring the user record history based on the set build date comprises:
- determining the set build date based on an availability of data in the user record history;
- determining a respective periodic status check proximity at each of the periodic status checks by:
- retrieving a time stamp for each periodic status check of the periodic status checks;
- and
- comparing the time stamp to the set build date;
- determining a respective re-censoring probability at each of the periodic status checks based on the respective periodic status check proximity;
- and
- determining whether a respective user record status at each of the periodic status checks is available based on the respective periodic status check proximity;
- generating a feature input for the user record history based on the respective user record status at each of the periodic status checks that is available in the re-censored record history;
- processing the feature input using a first model;
- receiving a first output of the first model indicating the respective probabilities that the user record for the user belongs to each of the plurality of user record states;
- and
- generating a recommendation based on the first output.
14 more elements
One or more non-transitory, computer-readable mediums comprising instructions that, when executed by one or more processors, cause operations comprising:
- receiving a request to determine respective probabilities that a user record for a user belongs to each of a plurality of user record states;
- retrieving a user record history for the user record, wherein the user record history comprises periodic status checks, wherein each of the periodic status checks comprises a status check date;
- determining that the user record history comprises a bias associated with the periodic status checks;
- in response to determining that the user record history comprises a bias, generating a re-censored record history by re-censoring the user record history based on a set build date, wherein generating the re-censored record history by re-censoring the user record history based on the set build date comprises:
- determining the set build date based on an availability of data in the user record history;
- determining a respective periodic status check proximity at each of the periodic status checks by:
- retrieving a time stamp for each periodic status check of the periodic status checks;
- and
- comparing the time stamp to the set build date;
- determining a respective re-censoring probability at each of the periodic status checks based on the respective periodic status check proximity;
- and
- determining whether a respective user record status at each of the periodic status checks is available based on the respective periodic status check proximity;
- generating a feature input for the user record history based on the respective user record status at each of the periodic status checks that is available in the re-censored record history;
- processing the feature input using a first model;
- receiving a first output of the first model indicating the respective probabilities that the user record for the user belongs to each of the plurality of user record states;
- and
- generating a recommendation based on the first output.
14 more elements
Dependencies are inferred from the claim text.