Improving supervised machine learning for materials science
Despite the widespread applications of machine learning models in materials science, in many cases the performance of machine learning models is not sufficiently accurate enough to meet the needs of materials design. In this thesis, we propose and apply a series of strategies to exam and improve upo...
Main Author: | Gong, Sheng |
---|---|
Other Authors: | Grossman, Jeffrey C. |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2023
|
Online Access: | https://hdl.handle.net/1721.1/147240 |
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