Training machine learning models with fairness improvement
AssigneeSocial Finance, Inc. dba SoFi
InventorsYonghan Feng, Sijia Liu, Ratinder Bedi, Aaron Webster
Life of this patent
Estimating the term…
Abstract
A method including training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics. The method also can include receiving real-time data. The method additionally can include outputting a risk score generated based on the machine-learning model, as trained, and the real-time data. Other embodiments are described.
Claims20
A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:
- training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics;
- receiving real-time data;
- and
- outputting a risk score generated based on the machine-learning model, as trained, and the real-time data.
A computer-implemented method comprising:
- training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics;
- receiving real-time data;
- and
- outputting a risk score generated based on the machine-learning model, as trained, and the real-time data.
Dependencies are inferred from the claim text.