Invention Grant
- Patent Title: Parameter-dependent model-blending with multi-expert based machine learning and proxy sites
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Application No.: US14798824Application Date: 2015-07-14
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Publication No.: US10592818B2Publication Date: 2020-03-17
- Inventor: Hendrik F. Hamann , Youngdeok Hwang , Levente Klein , Jonathan Lenchner , Siyuan Lu , Fernando J. Marianno , Gerald J. Tesauro , Theodore G. van Kessel
- 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: Cantor Colburn LLP
- Agent Vazken Alexanian
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F17/50 ; G06F16/28 ; G06F17/10

Abstract:
A parameter-based multi-model blending method and system are described. The method includes selecting a parameter of interest among parameters estimated by each of a set of individual models, running the set of individual models with a range of inputs to obtain a range of estimates of the parameters from each of the set of individual models, and identifying, for each of the set of individual models, critical parameters among the parameters estimated, the critical parameters exhibiting a specified correlation with an error in estimation of the parameter of interest. For each subspace of combinations of the critical parameters, obtaining a parameter-based blended model is based on blending the set of individual models in accordance with the subspace of the critical parameters, the subspace defining a sub-range for each of the critical parameters.
Public/Granted literature
- US20170017895A1 PARAMETER-DEPENDENT MODEL-BLENDING WITH MULTI-EXPERT BASED MACHINE LEARNING AND PROXY SITES Public/Granted day:2017-01-19
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