class_docstr: LED stream generator with concept drift.
  
  This class is an extension of the `LED` generator whose purpose is to add
  concept drift to the stream.
  
  Parameters
  ----------
  seed
      Random seed for reproducibility.
  noise_percentage
      The probability that noise will happen in the generation. At each
      new sample generated, a random number is generated, and if it is equal
      or less than the noise_percentage, the led value  will be switched
  irrelevant_features
      Adds 17 non-relevant attributes to the stream.
  n_drift_features
      The number of attributes that have drift.
  
  Examples
  --------
  >>> from river.datasets import synth
  
  >>> dataset = synth.LEDDrift(seed = 112, noise_percentage = 0.28,
  ...                          irrelevant_features= True, n_drift_features=4)
  
  >>> for x, y in dataset.take(5):
  ...     print(list(x.values()), y)
  [1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1] 7
  [1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0] 6
  [0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1] 1
  [1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1] 6
  [1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0] 7
  
  Notes
  -----
  An instance is generated based on the parameters passed. If `has_noise`
  is set then the total number of attributes will be 24, otherwise there will
  be 7 attributes.
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code: def __init__(
      self,
      seed: int | None = None,
      noise_percentage: float = 0.0,
      irrelevant_features: bool = False,
      n_drift_features: int = 0,
  ):
      super().__init__(
          seed=seed,
          noise_percentage=noise_percentage,
          irrelevant_features=irrelevant_features,
      )
      self.n_drift_features = n_drift_features
  
file_path: river/river/datasets/synth/led.py
imports: from __future__ import annotations
  import random
  from river import datasets
label_desc: Use image node_id 1 to create a new LEDDrift object from inherited base classes: LED with example: obj = LEDDrift(seed, noise_percentage, irrelevant_features, n_drift_features)