Hello,
I’m trying to train a cluster expansion with the species as Li, Mn, Ti, O and F with the primitive cell being that of rocksalt (primitive_structure = bulk(‘NaCl’,‘rocksalt’,a=3.0)).
All the structures are generated using icet.tools.enumerator.
I’m using cutoffs = [7.1,4,4].
My cluster space has 1032 parameters.
If I train my cluster expansion with less than 1032 structures, I get a underdetermined warning.
However, when I train my cluster expansion with more than 1032 structures, I get a condition number is large warning.
I read in the documentation that the cluster expansion is unreliable if the condition number is large.
To mitigate this, I scanned the pair cutoffs from 4 to 10 angstrom, and all the cases give the condition number is large warning.
My rmse_validation is low (around 0.09 eV/atom), and if I test it on new structures, the test rmse is lower than rmse_validation.
In this case, can the cluster expansion be trusted?
Thank you.