.. _`Multi-output Classifier`:

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

Multi-output Classifier
~~~~~~~~~~~~~~~~~~~~~~~

.. image:: multioutput.svg
   :width: 48


Fits one classifier for each target of outputs. Useful for extending classifiers that do not natively support multiple outputs



**Documentation**

Fits one classifier for each target of outputs. Useful for extending classifiers that do not natively support multiple outputs

*Configuration*:


  - *n_jobs*

    The number of jobs to run in parallel.
    :meth:`fit`, :meth:`predict` and :meth:`partial_fit` (if supported
    by the passed estimator) will be parallelized for each target.

    When individual estimators are fast to train or predict,
    using ``n_jobs > 1`` can result in slower performance due
    to the parallelism overhead.

    ``None`` means `1` unless in a :obj:`joblib.parallel_backend` context.
    ``-1`` means using all available processes / threads.
    See n_jobs for more details.

    .. versionchanged:: 0.20
        `n_jobs` default changed from `1` to `None`.




*Attributes*:




*Input ports*:
    **model** : model
        model

*Output ports*:
    **out-model** : model
        Output model


**Definition**


*Input ports*

    :model: 1 - 1,  model

        model


*Output ports*

    :out-model:  model

        Output model





.. automodule:: node_ensemble
    :noindex:

.. class:: MultiOutputClassifier
    :noindex: