XGBoost model for electrocaloric temperature change prediction in ceramics

An eXtreme Gradient Boosting (XGBoost) machine learning model is built to predict the electrocaloric (EC) temperature change of a ceramic based on its composition (encoded by Magpie elemental properties), dielectric constant, Curie temperature, and characterization conditions. A dataset of 97 EC cer...

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Bibliographic Details
Main Authors: Chu, S. (Author), Gong, J. (Author), McGaughey, A.J.H (Author), Mehta, R.K (Author)
Format: Article
Language:English
Published: Nature Research 2022
Subjects:
Online Access:View Fulltext in Publisher