Hi all,
I know that this isn't the best forum for this, but I am stuck and was
hopeful that someone else has made it through this.
I have been able to build models via scikit-learn with the RDKit python
wrappers. That all works beautifully! What I am struggling to get are the
weights, or scalers, applied to each bit position. For a SVM regression
model (SVR) I think that the values I seek are in the coef_ (if the model
is created via the linear kernel). But, all I get is something like this
when I print that out:
[[-0. -0.87146158 -0.46331996 ..., 0.31076767 -0.
-0.81882195]]
Has anyone flipped this back into an array, or am I looking at the wrong
thing here? Forgive my weak python skills for not knowing how to do this
automatically, it has been an extremely long time since I have written this
much python. (And I should add I have burned an incredible amount of time
looking for example code doing exactly this.)
Thanks!
Matthew
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