GLM-NET Gaussian Regression Classifier.
This is the GLM-NET algorithm from
Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent. http://www-stat.stanford.edu/~hastie/Papers/glmnet.pdf
parameterized to be a regression.
See GLMNET_C for the multinomial classifier version.
Notes
Available conditional attributes:
(Conditional attributes enabled by default suffixed with +)
Methods
clone() | Create full copy of the classifier. |
generate(ds) | Yield processing results. |
get_postproc() | Returns the post-processing node or None. |
get_sensitivity_analyzer(**kwargs) | Returns a sensitivity analyzer for GLMNET. |
get_space() | Query the processing space name of this node. |
is_trained([dataset]) | Either classifier was already trained. |
predict(obj, data, *args, **kwargs) | |
repredict(obj, data, *args, **kwargs) | |
reset() | |
retrain(dataset, **kwargs) | Helper to avoid check if data was changed actually changed |
set_postproc(node) | Assigns a post-processing node |
set_space(name) | Set the processing space name of this node. |
summary() | Providing summary over the classifier |
train(ds) | The default implementation calls _pretrain(), _train(), and finally _posttrain(). |
untrain() | Reverts changes in the state of this node caused by previous training |
Initialize | |
See |
Parameters : | family : {gaussian, multinomial}, optional
alpha : float, optional
nlambda : int, optional
standardize : bool, optional
thresh : float, optional
pmax : int or None, optional
maxit : int, optional
model_type : {covariance, naive}, optional
enable_ca : None or list of str
disable_ca : None or list of str
auto_train : bool
force_train : bool
space : str, optional
pass_attr : str, list of str|tuple, optional
postproc : Node instance, optional
descr : str
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Methods
clone() | Create full copy of the classifier. |
generate(ds) | Yield processing results. |
get_postproc() | Returns the post-processing node or None. |
get_sensitivity_analyzer(**kwargs) | Returns a sensitivity analyzer for GLMNET. |
get_space() | Query the processing space name of this node. |
is_trained([dataset]) | Either classifier was already trained. |
predict(obj, data, *args, **kwargs) | |
repredict(obj, data, *args, **kwargs) | |
reset() | |
retrain(dataset, **kwargs) | Helper to avoid check if data was changed actually changed |
set_postproc(node) | Assigns a post-processing node |
set_space(name) | Set the processing space name of this node. |
summary() | Providing summary over the classifier |
train(ds) | The default implementation calls _pretrain(), _train(), and finally _posttrain(). |
untrain() | Reverts changes in the state of this node caused by previous training |