.. _sphx_glr_auto_examples_ex_anonymous_transformer.py:


===============================
Anonymous transformers in skoot
===============================

Sometimes you have a pre-processing stage that finds itself awkwardly
positioned in the middle of your pipeline and you're left with one of
two options:

  1. Write a full transformer class
  2. Break your pipeline up into pieces

Obviously, the preferable action is the first, however many times your
function doesn't actually fit any training set parameters, so the transformer
feels like overkill.

This tutorial will introduce you to making anonymous, lightweight transformers
on the fly that will fit into your modeling pipeline seamlessly.

.. raw:: html

   <br/>





.. rst-class:: sphx-glr-script-out

 Out::

    Absolute scaled values: 
         StandardScaler1  ...  StandardScaler4
    73          0.354517  ...         0.022248
    18          0.133071  ...         1.179118
    118         2.304867  ...         1.490583
    78          0.232620  ...         0.422703
    76          1.207795  ...         0.289218
    31          0.498762  ...         1.045633
    64          0.254968  ...         0.155733
    141         1.329692  ...         1.490583
    68          0.476414  ...         0.422703
    82          0.011174  ...         0.022248
    110         0.842104  ...         1.090128
    12          1.230143  ...         1.446088
    36          0.376865  ...         1.312603
    9           1.108246  ...         1.446088
    19          0.864452  ...         1.179118
    56          0.598311  ...         0.556188
    104         0.842104  ...         1.357098
    69          0.254968  ...         0.111238
    55          0.133071  ...         0.155733
    132         0.720208  ...         1.357098
    29          1.352040  ...         1.312603
    127         0.354517  ...         0.823158
    26          0.986349  ...         1.045633
    128         0.720208  ...         1.223613
    131         2.548661  ...         1.090128
    145         1.085898  ...         1.490583
    108         1.085898  ...         0.823158
    143         1.207795  ...         1.490583
    45          1.230143  ...         1.179118
    30          1.230143  ...         1.312603

    [30 rows x 4 columns]




|


.. code-block:: python

    print(__doc__)

    # Author: Taylor Smith <taylor.smith@alkaline-ml.com>

    # #############################################################################
    # Introduce an interesting scenario
    from sklearn.model_selection import train_test_split
    from sklearn.pipeline import Pipeline
    from skoot.preprocessing import SelectiveStandardScaler
    from skoot.base import make_transformer
    from skoot.datasets import load_iris_df

    X = load_iris_df(tgt_name="target")
    y = X.pop('target')
    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42,
                                                        test_size=0.2)

    # Let's say we want to scale our features with the StandardScaler, but
    # for whatever reason we only want the ABSOLUTE value of the scaled values.
    # We *could* create a transformer or split our pipeline, but either case is
    # klunky and could interrupt our CV process in a grid search.
    #
    # So we'll instead define a simple commutative function that will be wrapped
    # in an "anonymous" transformer
    def make_abs(X):
        return X.abs()


    pipe = Pipeline([
        ("scale", SelectiveStandardScaler()),
        ("abs", make_transformer(make_abs))
    ])

    pipe.fit(X_train, y_train)
    print("Absolute scaled values: ")
    print(pipe.transform(X_test))

**Total running time of the script:** ( 0 minutes  0.017 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: ex_anonymous_transformer.py <ex_anonymous_transformer.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: ex_anonymous_transformer.ipynb <ex_anonymous_transformer.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_