Benchmark AFLOW Data Sets for Machine Learning
Volume: 9, Issue: 2, Pages: 153 - 156
Published: May 27, 2020
Abstract
Materials informatics is increasingly finding ways to exploit machine learning algorithms. Techniques such as decision trees, ensemble methods, support vector machines, and a variety of neural network architectures are used to predict likely material characteristics and property values. Supplemented with laboratory synthesis, applications of machine learning to compound discovery and characterization represent one of the most promising research...
Paper Details
Title
Benchmark AFLOW Data Sets for Machine Learning
Published Date
May 27, 2020
Volume
9
Issue
2
Pages
153 - 156
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