class_docstr: A matrix representation out of features.
class_docstr_tok: ["A","matrix","representation","out","of","features","."]
docstr: If there are 2 or more records with 0 distance from eachother - 
  keep only one. 
code: def remove_near_duplicates(self):
      """If there are 2 or more records with 0 distance from eachother -
      keep only one.
      """
  
      dist_matrix = self._distance(self.matrix)
  
      keeps = []
      dupes = set()
      for row_index in range(dist_matrix.shape[0]):
          max_dist = dist_matrix[row_index].max()
          for col_index in range(dist_matrix.shape[0]):
              if row_index < col_index:
                  if (
                      dist_matrix[row_index, col_index] / max_dist
                      <= 0.001
                  ):
                      dupes.add(col_index)
          if not row_index in dupes:
              keeps.append(row_index)
  
      self.matrix = self.matrix[keeps]
      self.records = self.records_data[keeps]
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import abc
  import numpy
  import scipy.sparse
  import scipy.spatial.distance
label_desc: Use image node_id 9 for calling the MatrixMetricSearch obj's underlying member method code with example usage: obj.remove_near_duplicates() without return types