To make use of GLMNET, you must have R and RPy installed as well
as both the glmnet contributed package. You can install the R and
RPy with the following command on Debian-based machines:
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Inherited from base.Classifier :
__repr__ ,
__str__ ,
clone ,
isTrained ,
predict ,
repredict ,
retrain ,
summary ,
train ,
trained ,
untrain
Inherited from misc.state.ClassWithCollections :
__getattribute__ ,
__new__ ,
__setattr__ ,
reset
Inherited from object :
__delattr__ ,
__format__ ,
__hash__ ,
__reduce__ ,
__reduce_ex__ ,
__sizeof__ ,
__subclasshook__
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_clf_internals = ['glmnet', 'linear', 'has_sensitivity', 'does...
Describes some specifics about the classifier -- is that it is
doing regression for instance....
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family = Parameter('gaussian', allowedtype= 'basestring', choi...
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alpha = Parameter(1.0, min= 0.01, max= 1.0, allowedtype= 'floa...
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nlambda = Parameter(100, allowedtype= 'int', min= 1, doc= """M...
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standardize = Parameter(True, allowedtype= 'bool', doc= """Whe...
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thresh = Parameter(1e-4, min= 1e-10, max= 1.0, allowedtype= 'f...
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pmax = Parameter(None, min= 1, allowedtype= 'None or int', doc...
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maxit = Parameter(100, min= 10, allowedtype= 'int', doc= """Ma...
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model_type = Parameter('covariance', allowedtype= 'basestring'...
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weights = property(lambda self: self.__weights)
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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
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