Package PyML :: Package feature_selection :: Module featsel :: Class MultiplicativeUpdate
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Class MultiplicativeUpdate

source code

     object --+    
              |    
FeatureSelector --+
                  |
                 MultiplicativeUpdate

Multiplicative update uses the vector w of an SVM to do feature selection. At each iteration an svm is trained and the data is multiplied by the weight vector of the classifier.

Reference:

J. Weston, A. Elisseeff, M. Tipping and B. Scholkopf. Use of the zero norm with linear models and kernel methods. JMLR special Issue on Variable and Feature selection, 2002.

Instance Methods
 
__init__(self, arg=None, **settings)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature
source code
 
__repr__(self)
repr(x)
source code
 
__iter__(self) source code
 
initialize(self, data) source code
 
next(self) source code
 
selectFeatures(self, data, *options, **args)
XXX for multi-class -- do one against the rest and use the absolute value of the average/maximum value of w to rescale multi-class
source code

Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __str__

    Inherited from FeatureSelector
 
rank(self, data, **args)
Returns: a ranking of the features in the dataset by converting the scores to ranks
source code
 
score(self, data, **args)
Returns: a score for each feature in the input dataset
source code
 
select(self, data, *options, **args)
invokes selectFeatures to find predictive features and eliminates the rest of the features from the input dataset
source code
 
test(self, data, *options, **args) source code
 
train(self, data, *options, **args)
invokes selectFeatures to find predictive features and eliminates the rest of the features from the input dataset
source code
Class Variables
    Inherited from FeatureSelector
  type = 'featureSelector'
Properties

Inherited from object: __class__

Method Details

__init__(self, arg=None, **settings)
(Constructor)

source code 

x.__init__(...) initializes x; see x.__class__.__doc__ for signature

Overrides: object.__init__
(inherited documentation)

__repr__(self)
(Representation operator)

source code 

repr(x)

Overrides: object.__repr__
(inherited documentation)

selectFeatures(self, data, *options, **args)

source code 
XXX for multi-class -- do one against the rest and use the absolute value of the average/maximum value of w to rescale multi-class
Returns:
a list of predictive features
Overrides: FeatureSelector.selectFeatures