Scaler
======

.. class:: Scaler(self, algorithm: Literal['standard', 'minmax', 'maxabs', 'robust', 'normalizer', 'power', 'quantile', 'quantile_normal'] = 'standard', **kwargs)

Scaler Wrapper class  - parent class :class:`Data`

.. list-table::
   :widths: 25 75
   :header-rows: 0

   * - Parameters
     - 
        algorithm : {"standard", "minmax", "maxabs", "robust", "normalizer", "power", "quantile", "quantile_normal"},                 default="standard"
            which scaling algorithm to use:
            - 'standard': StandardScaler
            - 'minmax': MinMaxScaler
            - 'maxabs': MaxAbsScaler
            - 'robust': RobustScaler
            - 'normalizer': Normalizer
            - 'power': PowerTransformer with method="yeo-johnson"
            - 'quantile': QuantileTransformer (default of QuantileTransformer)
            - 'quantile_normal': QuantileTransformer with output_distribution="normal" (gaussian pdf)

        \*\*kwargs:
            additional parameters for scaler
        

   * - Attributes
     - 
         
        algorithm : str
            name of the used algorithm
        
       
         
        transformer : transformer instance
            transformer instance (e.g. StandardScaler)
        
       



.. raw:: html

   <h2>Example</h2>

>>> from sam_ml.data.preprocessing import Scaler
>>>
>>> model = Scaler()
>>> print(model)
Scaler()
        

.. raw:: html

   <h2>Methods</h2>

.. list-table::
   :widths: 25 75
   :header-rows: 1

   * - Method
     - Description
   
   * - :meth:`~sam_ml.data.preprocessing.scaler.Scaler.get_params`
     - Function to get the parameter from the transformer instance
   
   * - :meth:`~sam_ml.data.preprocessing.scaler.Scaler.params`
     - Function to get the possible parameter values for the class
   
   * - :meth:`~sam_ml.data.preprocessing.scaler.Scaler.scale`
     - Function to scale/normalise data
   
   * - :meth:`~sam_ml.data.preprocessing.scaler.Scaler.set_params`
     - Function to set the parameter of the transformer instance
   




.. automethod:: sam_ml.data.preprocessing.scaler.Scaler.get_params

.. automethod:: sam_ml.data.preprocessing.scaler.Scaler.params

.. automethod:: sam_ml.data.preprocessing.scaler.Scaler.scale

.. automethod:: sam_ml.data.preprocessing.scaler.Scaler.set_params