missing features for prediction

[ppdebreuck]

If some features are missing (from the optimal ones), when featurizing novel compounds (for predicting stage), predict() will not work. This happens for instance when some elements are not present in this prediction set, and corresponding features are thus not generated, but could have been selected during training.

[ppdebreuck]

Issue still present - can now be elegantly fixed by using (or adapting) our Imputer to remember and impute missing features needed for prediction.
Sidenotes:

• It would be better though that non-existing features (such as Miedema statistics) are fixed at the root (either update matminer or not use at all).
• Imputation might be feature dependent... case (i) as above: unknown: replace by mean, -1,... Case (ii): missing but known: e.g. Element Fraction of missing element: obviously 0.

[ppdebreuck]

Tagging @gbrunin as partially involved in this.