CrabNet outperforms MODNet and random forest models when predicting battery electrode properties from composition, with cross-validation and clustering confirming coherent groupings.
Figure 4 shows a 2D-map of the t-SNE embeddings of MODNet and CrabNet features
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Machine Learning for Electrode Materials: Property Prediction via Composition
CrabNet outperforms MODNet and random forest models when predicting battery electrode properties from composition, with cross-validation and clustering confirming coherent groupings.