.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/mlearning/clustering_model/plot_gaussian_mixture.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_mlearning_clustering_model_plot_gaussian_mixture.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_mlearning_clustering_model_plot_gaussian_mixture.py:


Gaussian Mixtures
=================

Load Iris dataset and create clusters.

.. GENERATED FROM PYTHON SOURCE LINES 28-42

.. code-block:: Python


    from __future__ import annotations

    from numpy import array

    from gemseo import configure_logger
    from gemseo import create_benchmark_dataset
    from gemseo.datasets.dataset import Dataset
    from gemseo.mlearning import create_clustering_model
    from gemseo.post.dataset.scatter_plot_matrix import ScatterMatrix

    configure_logger()






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

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 43-46

Create dataset
--------------
We import the Iris benchmark dataset through the API.

.. GENERATED FROM PYTHON SOURCE LINES 46-48

.. code-block:: Python

    iris = create_benchmark_dataset("IrisDataset")








.. GENERATED FROM PYTHON SOURCE LINES 49-50

Extract inputs as a new dataset

.. GENERATED FROM PYTHON SOURCE LINES 50-54

.. code-block:: Python

    data = iris.get_view(group_names=iris.PARAMETER_GROUP).to_numpy()
    variables = iris.get_variable_names(iris.PARAMETER_GROUP)
    variables





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

 .. code-block:: none


    ['petal_length', 'petal_width', 'sepal_length', 'sepal_width']



.. GENERATED FROM PYTHON SOURCE LINES 55-57

.. code-block:: Python

    dataset = Dataset.from_array(data, variables)








.. GENERATED FROM PYTHON SOURCE LINES 58-62

Create clustering model
-----------------------
We know that there are three classes of Iris plants.
We will thus try to identify three clusters.

.. GENERATED FROM PYTHON SOURCE LINES 62-66

.. code-block:: Python

    model = create_clustering_model("GaussianMixture", data=dataset, n_components=3)
    model.learn()
    model






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div style='background-color: #fafae2; padding: 10px;'>GaussianMixture(n_components=3, random_state=0, var_names=None)<br/><ul><li>based on the scikit-learn library</li><li>built from 150 learning samples</li></ul></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 67-70

Predict output
--------------
Once it is built, we can use it for prediction.

.. GENERATED FROM PYTHON SOURCE LINES 70-79

.. code-block:: Python

    input_value = {
        "sepal_length": array([4.5]),
        "sepal_width": array([3.0]),
        "petal_length": array([1.0]),
        "petal_width": array([0.2]),
    }
    output_value = model.predict(input_value)
    output_value





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

 .. code-block:: none


    2



.. GENERATED FROM PYTHON SOURCE LINES 80-83

Plot clusters
-------------
Show cluster labels

.. GENERATED FROM PYTHON SOURCE LINES 83-85

.. code-block:: Python

    dataset.add_variable("gm_specy", model.labels.reshape((-1, 1)), "labels")
    ScatterMatrix(dataset, kde=True, classifier="gm_specy").execute(save=False, show=True)



.. image-sg:: /examples/mlearning/clustering_model/images/sphx_glr_plot_gaussian_mixture_001.png
   :alt: plot gaussian mixture
   :srcset: /examples/mlearning/clustering_model/images/sphx_glr_plot_gaussian_mixture_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    [<Figure size 640x480 with 16 Axes>]




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.647 seconds)


.. _sphx_glr_download_examples_mlearning_clustering_model_plot_gaussian_mixture.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

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

    .. container:: sphx-glr-download sphx-glr-download-python

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


.. only:: html

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

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