Data for: Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system
Published: 16 January 2019| Version 2 | DOI: 10.17632/82b9cczbm2.2
This data repository provides the raw and standardized data for machine learning presented in the article entitled "Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system" by the same authors. The data are generated by the cluster expansion method. The binary data, which are separated as the training set and test set, are used to construct the extremely randomized trees and deep neural networks models. And the ternary data of different temperatures are used for predictions.
Alloys, Machine Learning, Elastic Property