.. _`Normalizer`:

.. _`org.sysess.sympathy.machinelearning.normalizer`:

Normalizer
~~~~~~~~~~

.. image:: normalizer.svg
   :width: 48



Normalize samples individually to unit norm.

Each sample (i.e. each row of the data matrix) with at least one non
zero component is rescaled independently of other samples so that its
norm (l1, l2 or max) equals one.



**Documentation**

Normalize samples individually to unit norm.

Each sample (i.e. each row of the data matrix) with at least one non
zero component is rescaled independently of other samples so that its
norm (l1, l2 or max) equals one.

*Configuration*:


  - *norm*

    The norm to use to normalize each non zero sample. If norm='max'
    is used, values will be rescaled by the maximum of the absolute
    values.




*Attributes*:




*Input ports*:


*Output ports*:
    **model** : model
        Model


**Definition**


*Input ports*


*Output ports*

    :model:  model

        Model





.. automodule:: node_preprocessing
    :noindex:

.. class:: Normalizer
    :noindex: