Hey @Chryston_Boo!

Getting comprehensive info about the generated features can be done on a few different levels:

You can inspect the featurizer sets from this source file: automatminer/sets.py at c68ea8d966b3163cc44ba0e811951de97bbf1a23 · hackingmaterials/automatminer · GitHub

For info on each of the featurizers applied, see the matminer table of featurizers

For info on each of the featurizers applied, see the matminer source code, for example in the CoulombMatrix featurizer:

```
class CoulombMatrix(BaseFeaturizer):
"""
The Coulomb matrix, a representation of nuclear coulombic interaction.
Generate the Coulomb matrix, M, of the input structure (or molecule). The
Coulomb matrix was put forward by Rupp et al. (Phys. Rev. Lett. 108, 058301,
2012) and is defined by off-diagonal elements M_ij = Z_i*Z_j/|R_i-R_j| and
diagonal elements 0.5*Z_i^2.4, where Z_i and R_i denote the nuclear charge
and the position of atom i, respectively.
Coulomb Matrix features are flattened (for ML-readiness) by default. Use
fit before featurizing to use flattened features. To return the matrix form,
set flatten=False.
Args:
diag_elems (bool): flag indication whether (True, default) to use
the original definition of the diagonal elements; if set to False,
the diagonal elements are set to 0
flatten (bool): If True, returns a flattened vector based on eigenvalues
of the matrix form. Otherwise, returns a matrix object (single
feature), which will likely need to be processed further.
"""
```

For even more info, you can look at the citations for each of the featurizers which is applied, which will direct you to a peer reviewed publication giving as many details as you could want.