International Business Machines Corporation

Gandhi Sivakuma

Magesh Rajamani

Ramanakumar Natarajan

An embodiment for managing machine learning models to generate and utilize perforations within machine learning models to improve their ability to consider and learn from exception decisions. The embodiment may detect an exception decision in a base model. The embodiment may automatically determine data considered in making the exception decision and identify and store in a database known features from the gathered data. The embodiment may automatically identify and store in the database remaining additional features considered, and generate and store perforations corresponding to the remaining additional features considered. The embodiment may, in response to detecting subsequent decisions involving shared additional features contained in the generated perforations, automatically validate feature boundaries within the generated perforations from a set of data sources. The embodiment may automatically calculate scores for the subsequent decisions using both the base model and corresponding perforation and output decision recommendations for the subsequent decisions.

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Bentleigh, Australia

Gandhi Sivakuma