Mapper to select a subset of features.
Depending on the actual slicing two FeatureSelections can be merged in a number of ways: incremental selection (+=), union (&=) and intersection (|=). Were the former assumes that two feature selections are applied subsequently, and the latter two assume that both slicings operate on the set of input features.
Notes
Available conditional attributes:
(Conditional attributes enabled by default suffixed with +)
Examples
>>> from mvpa2.datasets import *
>>> ds = Dataset([[1,2,3,4,5]])
>>> fs0 = StaticFeatureSelection([0,1,2,3])
>>> fs0(ds).samples
array([[1, 2, 3, 4]])
Merge two incremental selections: the resulting mapper performs a selection that is equivalent to first applying one slicing and subsequently the next slicing. In this scenario the slicing argument of the second mapper is relative to the output feature space of the first mapper.
>>> fs1 = StaticFeatureSelection([0,2])
>>> fs0 += fs1
>>> fs0(ds).samples
array([[1, 3]])
Parameters : | filler : optional
enable_ca : None or list of str
disable_ca : None or list of str
auto_train : bool
force_train : bool
space: str, optional :
postproc : Node instance, optional
descr : str
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