Comments (1)
probably using scaled deviance is enough!
from pygam.
Related Issues (20)
- Adding new penalty terms HOT 3
- Is this project being actively maintained? HOT 2
- Specifying terms in LinearGAM is incompatible with sklearn.compose.TransformedTargetRegressor (bug)
- B-spline basis and B-spline fitting plot HOT 1
- Documentation erroneously states that `coef_[0]` is the intercept (bias) HOT 1
- Version number hard coded HOT 1
- ValueError: cannot set WRITEABLE flag to True of this array HOT 2
- MAJOR BUG IN PYGAM VERSION 0.9.0 HOT 1
- Returning no terms when cloning the model
- Assessing significance of smooth terms with permutation testing
- When using s(): AttributeError: module 'numpy' has no attribute 'int'. HOT 3
- Non-pickle export option? HOT 1
- Inquiry on Discrepancies Between pyGAM and R GAM Model Results
- What does _pirls stand for in the LinearGAM.fit()?
- GAM Time complexity
- Default coefficient for a linear term
- GAM results of Pygam's GAM and mgcv GAM are not matching
- Received error 'csr_matrix' object has no attribute 'A' HOT 2
- Contribution of each smooth term
- Customizable GAM - missing functionalities that exist in mgcv
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from pygam.