Descriptors for machine learning of materials data

40Citations
Citations of this article
154Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Descriptors, which are representations of compounds, play an essential role in machine learning of materials data. Although many representations of elements and structures of compounds are known, these representations are difficult to use as descriptors in their unchanged forms. This chapter shows how compounds in a dataset can be represented as descriptors and applied to machine-learning models for materials datasets.

Cite

CITATION STYLE

APA

Seko, A., Togo, A., & Tanaka, I. (2018). Descriptors for machine learning of materials data. In Nanoinformatics (pp. 3–23). Springer Singapore. https://doi.org/10.1007/978-981-10-7617-6_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free