Open ghost opened 5 years ago
Hello @dswah : I came across your answer to another post that closely relates to my question, but on trying those suggested commands it seemed that some of those 'inner' functions (e.g. * _edge_knots
, * _n_splines
, etc.) did not work for me in the 0.8.0
version of pygam as I get AttributeError
for most of them. I think if those functions work along with pygam.utils.b_spline_basis
then that would be sufficient.
On a related note, I have another doubt: what does the numerical value pdep
that is the output of partial_dependence
indicate, which contains both negative and positive numerical values? It does not seem to be in the range that is obtained as an output from the fitted splines (gam.predict
).
I have the same issue with the 'inner' functions not working. I performed a grid search, and would like to know the order of the spline fit on each feature function. I cannot seem to be able to retrieve it anywhere.
Cheers
Hi @L4student, So if you read the attached documents referred to as reading material, you will understand that
I am using
pygam.gam( )
that is fitting all the features with splines (without my imposing any specificterm
to any feature), so is it fair to say that GAM is equivalent to multivariate adaptive regression splines (MARS) in this case? If that's true, then I am looking for the expanded form of the model equation that GAM fits on the data, which would be more than the coefficients of the splines (gam.coef_
). Specifically, I would like to knowpygam
that ensures there is no overfit of the model since I don't see the splines pruned from their default number (20 for each feature).I could not find anything on these two things either in the doc or the issues.