:orphan:

Examples
--------



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    <div class="sphx-glr-thumbcontainer" tooltip="Logging Example">

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  .. image:: /examples/images/thumb/sphx_glr_logging_thumb.png
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  :ref:`sphx_glr_examples_logging.py`

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      <div class="sphx-glr-thumbnail-title">Logging Example</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example will go over how to extract metadata which a clustering algorithm may have generated.">

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  .. image:: /examples/images/thumb/sphx_glr_cluster_meta_thumb.png
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  :ref:`sphx_glr_examples_cluster_meta.py`

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      <div class="sphx-glr-thumbnail-title">Getting clustering metadata</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Basic Use">

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  .. image:: /examples/images/thumb/sphx_glr_basic_thumb.png
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  :ref:`sphx_glr_examples_basic.py`

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      <div class="sphx-glr-thumbnail-title">Basic Use</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Extracting Data from Nodes">

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  .. image:: /examples/images/thumb/sphx_glr_extracting_data_thumb.png
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  :ref:`sphx_glr_examples_extracting_data.py`

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      <div class="sphx-glr-thumbnail-title">Extracting Data from Nodes</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example will go over the API for creating a custom cover scheme. We will be implementing the epsilon nets outlined in https://arxiv.org/abs/1901.07410. This is meant to illustrate the expected api, not much thought was put into the actual implementation of the cover itself and there may be better ways.">

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  .. image:: /examples/images/thumb/sphx_glr_custom_cover_thumb.png
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  :ref:`sphx_glr_examples_custom_cover.py`

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      <div class="sphx-glr-thumbnail-title">Creating a custom cover</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This example will go over the API for creating a clusterer. We will implement a density-based clusterer (no real thought was put into how useful of a clusterer this is). Given an epsilon &gt; 0, we calculate the number of neighbors a point has within an epsilon ball. We then cluster the dataset into k (num_clusters) sets, aiming to equally divide the number of possible neighbors. Note that two points being in the same cluster tells us nothing about their Euclidean distance.">

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  .. image:: /examples/images/thumb/sphx_glr_custom_clusterer_thumb.png
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  :ref:`sphx_glr_examples_custom_clusterer.py`

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      <div class="sphx-glr-thumbnail-title">Creating a custom clusterer</div>
    </div>


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    </div>


.. toctree::
   :hidden:

   /examples/logging
   /examples/cluster_meta
   /examples/basic
   /examples/extracting_data
   /examples/custom_cover
   /examples/custom_clusterer


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  .. container:: sphx-glr-footer sphx-glr-footer-gallery

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

      :download:`Download all examples in Python source code: examples_python.zip </examples/examples_python.zip>`

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

      :download:`Download all examples in Jupyter notebooks: examples_jupyter.zip </examples/examples_jupyter.zip>`


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

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