A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys
Abstract We demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative relationship between chemical composition an...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-07-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-15618-4 |