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

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Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

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__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

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_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