Mechanisms for continuous improvement of automated machine learning

• Main Authors: Kunc, Ladislav, Tan, Ming, Qi, Haode, Potdar, Saloni
• Format: Patent
• Language: English
• Published: 23.08.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

Mechanisms are provided for optimizing an automated machine learning (AutoML) operation to configure parameters of a machine learning model. AutoML logic is configured based on an initial default value and initial range for sampling of a parameter of the machine learning (ML) model and an initial AutoML process is executed on the ML model based on a plurality of datasets comprising a plurality of domains of data elements, utilizing the initially configured AutoML logic. For each domain, a cross-dataset default value and cross-dataset value range are derived from results of the execution of the initial AutoML process. For each domain, an entry is stored in a data structure, the entry storing the derived cross-dataset default value and cross-dataset value range for the domain. The AutoML logic performs a subsequent AutoML process on a new dataset based on one or more entries of the data structure.