.. _`Fit Transform`:

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

Fit Transform
`````````````

.. image:: transform.svg
   :width: 48


Fits a transform model to the given data and computes the transformed data. 




Documentation
:::::::::::::

Apply transform model to data. This node uses the models implemenation of the
.fit_transform() method, which is usually a combination of .fit() and .transform(). When you
call .fit_transform(X), the method first learns from the data (.fit()), and then applies the
transformation to X (.transform()), returning the modified version of the data. This node
should not be used with test data since it also trains the model.

Class lables can be supplied by enabeling the Y port: Ports > Input > Y in the configuration
GUI.


Definition
::::::::::


Input ports
...........

    **in-model**
        | Type: model
        | Description: Input model
    **input**
        | Type: table
        | Description: Input table
    **Y**
        | Type: table
        | Description: Y
        | Optional number of ports: 0--1 (default: 0)
        

Output ports
............

    **out-model**
        | Type: model
        | Description: Output model
    **output**
        | Type: table
        | Description: Output table



Configuration
.............

    **Output names** (names method)
        Method used to generate output names
    **Transpose output** (transpose)
        Transposes output data, suitable for large number of features (eg. word counts)







Examples
........





The node can be found in:

* :download:`Polynomial_Features.syx </Examples/Sympathy for Data/MachineLearning/Polynomial_Features.syx>`

* :download:`KmeansOutlierRemoval.syx </Examples/Advanced Machine Learning/KmeansOutlierRemoval.syx>`

* :download:`agglomerative_clustering.syx </Examples/Advanced Machine Learning/agglomerative_clustering.syx>`




Implementation
..............

.. automodule:: node_application
    :noindex:

.. class:: FitTransform
    :noindex: