code: def __init__(
      self,
      random_state: Optional[Union[int, np.random.RandomState]] = None,
  ) -> None:
      from sklearn.preprocessing import StandardScaler
  
      self.preprocessor = StandardScaler(copy=False)
  
file_path: auto-sklearn/autosklearn/pipeline/components/data_preprocessing/rescaling/standardize.py
imports: from typing import Dict, Optional, Tuple, Union
  import numpy
  from scipy import sparse
  from sklearn.exceptions import NotFittedError
  from autosklearn.pipeline.base import DATASET_PROPERTIES_TYPE, PIPELINE_DATA_DTYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.components.data_preprocessing.rescaling.abstract_rescaling import Rescaling
  from autosklearn.pipeline.constants import DENSE, INPUT, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 1 to create a new StandardScalerComponent object from inherited base classes: Rescaling, AutoSklearnPreprocessingAlgorithm with example: obj = StandardScalerComponent(random_state)