Advances in machine learning have made the classification process significantly less tedious and also opened up efficient ways of predicting materials with interesting properties based on basic ...

Following this, the basic features were transformed into z-vectors—information based on the paths taken by the RF model. And finally, cluster analysis was performed on the transformed z-vectors.

A new study introduced a machine learning-powered clustering model that incorporates both basic features and target properties, successfully grouping over 1,000 inorganic materials.