text: from sklearn.preprocessing import Normalizer as Nrm
  from niaaml.preprocessing.feature_transform.feature_transform_algorithm import (
      FeatureTransformAlgorithm,
  )
  from niaaml.utilities import ParameterDefinition
  
  __all__ = ["Normalizer"]
  
  
  class Normalizer(FeatureTransformAlgorithm):
      r"""Implementation of feature normalization algorithm.
  
      Date:
          2020
  
      Author:
          Luka Pečnik
  
      License:
          MIT
  
      Documentation:
          https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Normalizer
  
      See Also:
          * :class:`niaaml.preprocessing.feature_transform.FeatureTransformAlgorithm`
      """
      Name = "Normalizer"
  
      def __init__(self, **kwargs):
          r"""Initialize Normalizer."""
          self._params = dict(norm=ParameterDefinition(["l1", "l2", "max"]))
          self.__params = None
          self.__normalizer = Nrm()
  
      def set_parameters(self, **kwargs):
          r"""Set the parameters/arguments of the algorithm."""
          self.__params = kwargs
          self.__params["axis"] = 0
  
      def fit(self, x, **kwargs):
          r"""Fit implemented transformation algorithm.
  
          Arguments:
              x (pandas.core.frame.DataFrame): n samples to fit transformation algorithm.
          """
          self.__normalizer.fit(x)
  
      def transform(self, x, **kwargs):
          r"""Transforms the given x data.
  
          Arguments:
              x (pandas.core.frame.DataFrame): Data to transform.
  
          Returns:
              pandas.core.frame.DataFrame: Transformed data.
          """
          return self.__normalizer.transform(x)
  
      def to_string(self):
          r"""User friendly representation of the object.
  
          Returns:
              str: User friendly representation of the object.
          """
          return FeatureTransformAlgorithm.to_string(self).format(
              name=self.Name,
              args=self._parameters_to_string(self.__normalizer.get_params()),
          )
  