Package mvpa :: Package clfs :: Module glmnet :: Class GLMNET_R

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# Class GLMNET_R

source code

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.

Nested Classes | [hide private]

Inherited from `misc.state.ClassWithCollections`: `__metaclass__`

Instance Methods | [hide private]

__init__(self, **kwargs) Initialize GLM-Net. | source code

Inherited from `_GLMNET`: `getSensitivityAnalyzer`

Inherited from `_GLMNET` (private): `_getFeatureIds`, `_predict`, `_train`

Inherited from `base.Classifier`: `__repr__`, `__str__`, `clone`, `isTrained`, `predict`, `repredict`, `retrain`, `summary`, `train`, `trained`, `untrain`

Inherited from `base.Classifier` (private): `_postpredict`, `_posttrain`, `_prepredict`, `_pretrain`, `_regressionIsBogus`, `_setRetrainable`

Inherited from `misc.state.ClassWithCollections`: `__getattribute__`, `__new__`, `__setattr__`, `reset`

Inherited from `object`: `__delattr__`, `__format__`, `__hash__`, `__reduce__`, `__reduce_ex__`, `__sizeof__`, `__subclasshook__`

Class Variables | [hide private]

| _clf_internals = `_GLMNET._clf_internals+ ['regression']` Describes some specifics about the classifier -- is that it is doing regression for instance....

Inherited from `_GLMNET`: `alpha`, `family`, `maxit`, `model_type`, `nlambda`, `pmax`, `standardize`, `thresh`, `weights`

Inherited from `base.Classifier`: `_DEV__doc__`, `feature_ids`, `predicting_time`, `predictions`, `regression`, `retrainable`, `trained_dataset`, `trained_labels`, `trained_nsamples`, `training_confusion`, `training_time`, `values`

Inherited from `misc.state.ClassWithCollections`: `descr`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, **kwargs)
(Constructor)

source code

Initialize GLM-Net.

See the help in R for further details on the parameters

Overrides: object.__init__