Patent ID: 11941496
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for machine-learning model accuracy, comprising:
determining, by a computer processor and using a prediction accuracy machine-learning model, a first confidence that a first prediction generated, for a first data point of a client transaction, and by a classifier of a machine-learning model is accurate by:
generating, by the computer processor, prediction training data comprising, for each of a plurality of training transactions of the machine-learning model:
a data point;
a training prediction made by the classifier for the data point;
an indication whether the training prediction is accurate;
a first probability that the machine learning model determines that the training prediction is accurate; and
a second probability that that the machine learning model determines that an alternative prediction is accurate;

training, by the computer processor, the prediction accuracy machine-learning model to determine a client confidence that a client prediction generated by the machine-learning model is accurate using the prediction training data; and
generating, using the prediction accuracy machine-learning model:
a second prediction for the first data point; and
the first confidence, wherein the first confidence is equal to a second confidence that the second prediction is accurate;

wherein the first prediction represents a machine-learning classification of a corresponding client transaction.