Runtime estimation for machine learning data processing pipeline

US12299544B2 · kind B2 · utility

Assignee

• SAP SE · DE

Inventors

• Steven Jaeger · Heidelberg, DE
• Isil Pekel · Heidelberg, DE
• Manuel Zeise · Karlsruhe, DE

Key dates

• Filing date: Sep 24, 2020
• Grant date: May 13, 2025
• Expiry date: Dec 8, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/20
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Inputs may be received for constructing a data processing pipeline configured to implement an process to generate a machine learning model for performing a task associated with an input dataset. The process may include a plurality of machine learning trials, each of which applying, to a training dataset and/or a validation dataset generated based on the input dataset, a different type of machine learning model and/or a different set of trial parameters. The machine learning model being generated based on a result of the plurality of machine learning trials. A runtime estimate for the process to generate the machine learning model may be determined. The runtime estimate may enable the allocation of a sufficient time budget for the process. Moreover, the process may be executed if the runtime of the process does not exceed the available time budget.