class_docstr: Feature selection using data-mined expert knowledge.
  Based on the ReliefF algorithm as introduced in:
  Igor et al. Overcoming the myopia of inductive learning
  algorithms with RELIEFF (1997), Applied Intelligence, 7(1), p39-55
docstr: Scikit-learn required: Reduces the feature set down to the top `n_features_to_select` features.
  Parameters
  ----------
  X: array-like {n_samples, n_features}
      Feature matrix to perform feature selection on
  Returns
  -------
  X_reduced: array-like {n_samples, n_features_to_select}
      Reduced feature matrix
docstr_tok: ["Scikit-learn","required",":","Reduces","the","feature","set","down","to","the","top","`","n_features_to_select","`","features",".","Parameters","--","--","--","--","--","X",":","array-like","{","n_samples",",","n_features","}","Feature","matrix","to","perform","feature","selection","on","Returns","--","--","--","-","X_reduced",":","array-like","{","n_samples",",","n_features_to_select","}","Reduced","feature","matrix"]
code: def transform(self, X):
      """Scikit-learn required: Reduces the feature set down to the top `n_features_to_select` features.
      Parameters
      ----------
      X: array-like {n_samples, n_features}
          Feature matrix to perform feature selection on
      Returns
      -------
      X_reduced: array-like {n_samples, n_features_to_select}
          Reduced feature matrix
      """
      if self._num_attributes < self.n_features_to_select:
          raise ValueError(
              "Number of features to select is larger than the number of features in the dataset."
          )
  
      return X[:, self.top_features_[: self.n_features_to_select]]
  
imports: from __future__ import print_function
  import numpy
  import time
  import warnings
  import sys
  from sklearn.base import BaseEstimator
  from joblib import Parallel, delayed
  from .scoring_utils import get_row_missing, ReliefF_compute_scores, get_row_missing_iter
label_desc: Use image node_id 3 for calling the ReliefF obj's underlying member method code with example usage: obj.transform(X) and returns: X