Use a two-class feature selection method for multi-class problem
by doing feature selection in a one-against-the-rest manner, and
returns the union of all the features selected.
|
__init__(self,
featureSelector)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature |
source code
|
|
|
|
Inherited from object :
__delattr__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__str__
|
|
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
|
|
|
|
|
train(self,
data,
*options,
**args)
invokes selectFeatures to find predictive features and eliminates
the rest of the features from the input dataset |
source code
|
|