Fig. 4: The flowchart of our PF-based machine learning models.
From: Topological feature engineering for machine learning based halide perovskite materials design
The material structures are represented as simplicial complexes, based on which geometric and topological features are evaluated. The PF-based features, including PH fingerprint and PFC fingerprint, are combined with machine learning models, in particular GBT, to predict material properties.
