Machine-learning model retraining detection

An apparatus, comprising:

• at least one processor;
• and
• a computer readable storage medium having computer readable program code embodied therewith and executable by the at least one processor;
• wherein the computer readable program code is configured to obtain predictions generated by a deployed machine-learning model;
• wherein the computer readable program code is configured to generate, from the obtained predictions, a validation dataset comprising a plurality of data points, wherein the validation dataset is generated in view of user preferences related to desired performance metrics of the deployed machine-learning model;
• wherein the computer readable program code is configured to rank the plurality of data points of the validation dataset in view of the user preferences;
• wherein the computer readable program code is configured to determine the deployed machine-learning model needs to be retrained by comparing the ranked plurality of data points to a training dataset used to train the deployed machine-learning model and identifying, based upon the comparison, a quality of the deployed machine-learning model can be increased above a predetermined threshold;
• and
• wherein the computer readable program code is configured to retrain the deployed machine-learning model utilizing a new training dataset being based upon the validation dataset and the ranked plurality of data points.

A computer program product, comprising:

• a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code executable by a processor;
• wherein the computer readable program code is configured to obtain predictions generated by a deployed machine-learning model;
• wherein the computer readable program code is configured to generate, from the obtained predictions, a validation dataset comprising a plurality of data points, wherein the validation dataset is generated in view of user preferences related to desired performance metrics of the deployed machine-learning model;
• wherein the computer readable program code is configured to rank the plurality of data points of the validation dataset in view of the user preferences;
• wherein the computer readable program code is configured to determine the deployed machine-learning model needs to be retrained by comparing the ranked plurality of data points to a training dataset used to train the deployed machine-learning model and identifying, based upon the comparison, a quality of the deployed machine-learning model can be increased above a predetermined threshold;
• and
• wherein the computer readable program code is configured to retrain the deployed machine-learning model utilizing a new training dataset being based upon the validation dataset and the ranked plurality of data points.