class_docstr: Select a subset of features.
  
  The ``Subset`` class acts as a transformer that reduces the feature set
  to a subset specified by the user.
  
  Parameters
  ----------
  subset : list
      list of columns indexes to select subset with. Indexes can
      either be of type ``str`` if data accepts slicing on a list of
      strings, otherwise the list should be of type ``int``.
class_docstr_tok: ["Select","a","subset","of","features",".","The","``","Subset","``","class","acts","as","a","transformer","that","reduces","the","feature","set","to","a","subset","specified","by","the","user",".","Parameters","--","--","--","--","--","subset",":","list","list","of","columns","indexes","to","select","subset","with",".","Indexes","can","either","be","of","type","``","str","``","if","data","accepts","slicing","on","a","list","of","strings",",","otherwise","the","list","should","be","of","type","``","int","``","."]
code: def __init__(self, subset=None):
      self.subset = subset
  
file_path: mlens/mlens/preprocessing/preprocess.py
imports: from __future__ import division, print_function
  from ..externals.sklearn.base import BaseEstimator, TransformerMixin
label_desc: Use image node_id 1 to create a new Subset object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = Subset(subset)