minerva.analysis.clustering_analysis
====================================

.. py:module:: minerva.analysis.clustering_analysis


Classes
-------

.. autoapisummary::

   minerva.analysis.clustering_analysis.ClusteringAnalysis


Module Contents
---------------

.. py:class:: ClusteringAnalysis(data_split = 'predict')

   Bases: :py:obj:`minerva.analysis.model_analysis._ModelAnalysis`


   Perform a clustering analysis on the embeddings generated by some model,
   using the Silhouette score and Davies-Bouldin score, functions implemented
   in sklearn. The results are returned in a dictionary.

   Initialize the analysis with the specified data split.

   Parameters
   ----------
   data_split : str, optional
       The data split to use for the analysis, by default "predict".
       This specifies which part of the dataset to analyze. Can be one of:
       ["train", "validation", "test", "predict"].


   .. py:method:: compute(model, data)

      Compute the clustering analysis metrics.

      Parameters
      ----------
      model : L.LightningModule
          The trained model from which to extract embeddings.
      data : L.LightningDataModule
          The data module containing the dataset to analyze.
      Returns
      -------
      dict
          A dictionary containing the Silhouette score and Davies-Bouldin score.



   .. py:attribute:: data_split
      :value: 'predict'