Robotics & Machine Learning Daily News2024,Issue(Apr.8) :16-16.

Researchers from Argonne National Laboratory Describe Findings in Machine Learni ng (Evaluating Generalized Feature Importance Via Performance Assessment of Mach ine Learning Models for Predicting Elastic Properties of Materials)

Robotics & Machine Learning Daily News2024,Issue(Apr.8) :16-16.

Researchers from Argonne National Laboratory Describe Findings in Machine Learni ng (Evaluating Generalized Feature Importance Via Performance Assessment of Mach ine Learning Models for Predicting Elastic Properties of Materials)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating in Lemont, Illino is, by NewsRx journalists, research stated, “Identifying key descriptorsand und erstanding important features across different classes of materials are crucial for machine learning(ML) tools to both predict material properties and reveal t he physics underlying any process of interest.Traditionally, the predictive mod eling of elastic properties of materials is limited to only a few classes ofmat erials and a small set of ML tools despite the broad applications of these mater ials.”

Key words

Lemont/Illinois/United States/North a nd Central America/Cyborgs/Emerging Technologies/Machine Learning/Argonne Na tional Laboratory

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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