Invention Grant
- Patent Title: Automated machine learning pipeline generation
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Application No.: US16942247Application Date: 2020-07-29
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Publication No.: US11620582B2Publication Date: 2023-04-04
- Inventor: Bei Chen , Long Vu , Syed Yousaf Shah , Xuan-Hong Dang , Peter Daniel Kirchner , Si Er Han , Ji Hui Yang , Jun Wang , Jing James Xu , Dakuo Wang , Dhavalkumar C. Patel , Gregory Bramble , Horst Cornelius Samulowitz , Saket Sathe , Chuang Gan
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06N20/20
- IPC: G06N20/20

Abstract:
Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.
Public/Granted literature
- US20220036246A1 AUTOMATED MACHINE LEARNING PIPELINE GENERATION Public/Granted day:2022-02-03
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