Stochastic Replica Voting Machine prediction of stable Perovskite and binary alloys.
A machine learning approach that we term that the Stochastic Replica Voting Machine (SRVM) algorithm is presented and applied to a binary and a 3-class classification problems in materials science. Here, we employ SRVM to predict candidate compounds capable of forming cubic Perovskite (ABX3) structure and further classify binary (AB) solids. The results of our binary and ternary classifications compared to those obtained by the SVM algorithm.
Publisher URL: http://arxiv.org/abs/1705.08491
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