Managing machine learning models

Abstract

A method includes receiving files. Deployed models analyze the files to create results with corresponding data. The results identify suspicious files. The system calculates ranked results by ranking the results according to a confidence level, and clustered groups by clustering the results based on similar data. The system calculates classes by correlating the ranked results to the clustered groups. The classes indicate accurate results and inaccurate results. The system retrains the deployed models having the class indicating inaccurate results with new training sets to create retrained models. The system validates the retrained models when the retrained models identify one or more suspicious files from the receiving. The system compares the classes of the deployed models to new classes of the retrained models. The computerized system deploys the retrained models when the new classes of the retrained models indicate accurate results greater than the classes of the deployed models.

CPC Classifications