class_docstr: Scale each sample by its maximum absolute value.
  
  Examples
  --------
  >>> from pyts.preprocessing import MaxAbsScaler
  >>> X = [[1, 5, 3, 2, 10, 6, 4, 7],
  ...      [1, -5, 3, 2, 2, 1, 0, 2]]
  >>> scaler = MaxAbsScaler()
  >>> scaler.transform(X)
  array([[ 0.1,  0.5,  0.3,  0.2,  1. ,  0.6,  0.4,  0.7],
         [ 0.2, -1. ,  0.6,  0.4,  0.4,  0.2,  0. ,  0.4]])
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code: def __init__(self):
      pass
  
imports: from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.preprocessing import MaxAbsScaler
  from sklearn.preprocessing import RobustScaler
  from sklearn.utils.validation import check_array
  from ..base import UnivariateTransformerMixin
label_desc: Use image node_id 1 to create a new MaxAbsScaler object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = MaxAbsScaler()