
基本信息:
- 专利标题: MACHINE LEARNING PIPELINE OPTIMIZATION
- 申请号:US18100694 申请日:2023-01-24
- 公开(公告)号:US20230162289A1 公开(公告)日:2023-05-25
- 发明人: Alain Charles Briancon , Jean Joseph Belanger , Chris Coovey , Valisis Sotiris , Eric Simon
- 申请人: Cerebri AI Inc.
- 申请人地址: US TX Austin
- 专利权人: Cerebri AI Inc.
- 当前专利权人: Cerebri AI Inc.
- 当前专利权人地址: US TX Austin
- 主分类号: G06Q40/08
- IPC分类号: G06Q40/08 ; G06N20/00 ; G06F8/20 ; G06N20/20 ; G06F8/10 ; G06F8/30 ; G06F8/36 ; G06F16/25 ; G06F9/445 ; G06N5/04 ; G06Q10/0631 ; G06Q10/0637 ; G06Q10/0639 ; G06Q10/067 ; G06Q30/012 ; G06Q30/016 ; G06Q30/0204 ; G06Q30/0202 ; G06F18/214 ; G06F18/21 ; G06F18/243 ; G06Q40/03
摘要:
Provided is a process of modeling methods organized in racks of a machine learning pipeline to facilitate optimization of performance using modelling methods for implementation of machine learning design in an object-oriented modeling (OOM) framework, the process including: writing classes using object-oriented modelling of optimization methods, modelling methods, and modelling racks; writing parameters and hyper-parameters of the modeling methods as attributes as the modeling methods; scanning modelling racks classes to determine first class definition information; selecting a collection of rack and selecting modeling method objects; scanning modelling method classes to determine second class definition information; assigning racks and locations within the racks to modeling method objects; and invoking the class definition information to produce object manipulation functions that allow access the methods and attributes of at least some of the modeling method objects, the manipulation functions being configured to effectuate writing locations within racks and attributes of racks.