synthval.metrics
================

.. py:module:: synthval.metrics

.. autoapi-nested-parse::

   Module for computing various similarity metrics between two sets of samples originating from multivariate distributions.

   This module defines abstract and concrete classes for computing similarity metrics between samples from two
   distributions. The available metrics include Kullback-Leibler divergence, Wasserstein distance, Energy distance,
   Mean Mahalanobis distance, Frechet Distance, Inception Score, Kernel Distances and others.
   Given the scope of the package, we identify the first distribution as real_dist and the second as synth_dist indicating
   the distribution of the real data and the distribution of the synthetic data respectively.
   It should be noted that the methods of the package can be generally applied to any kind of multivariate distributions.

   Classes
   -------
   SimilarityMetric(abc.ABC)
       Abstract base class for defining similarity metrics.
   KLDivergenceEstimation(SimilarityMetric)
       Concrete implementation of Kullback-Leibler divergence estimation.
   WassersteinDistance(SimilarityMetric)
       Concrete implementation of the Wasserstein distance.
   EnergyDistance(SimilarityMetric)
       Concrete implementation of the Energy distance.
   MeanMahalanobisDistance(SimilarityMetric)
       Concrete implementation of the mean Mahalanobis distance.
   FCNNAccuracyMetric(SimilarityMetric)
       Concrete implementation of an accuracy metric based on fully-connected neural networks.
   InceptionScore()
       Evaluation metrics for generated images.
   FrechetDistance(SimilarityMetric)
       Concrete implementation of the Frechet distance.
   KernelDistance(SimilarityMetric)
       Concrete implementation of the Kernel distance.
   PRScore(SimilarityMetric)
       Concrete implementation of the Precision and Recall Scores.



Classes
-------

.. toctree::
   :hidden:

   /autoapi/synthval/metrics/SimilarityMetric
   /autoapi/synthval/metrics/KLDivergenceEstimation
   /autoapi/synthval/metrics/WassersteinDistance
   /autoapi/synthval/metrics/EnergyDistance
   /autoapi/synthval/metrics/MeanMahalanobisDistance
   /autoapi/synthval/metrics/FCNNAccuracyMetric
   /autoapi/synthval/metrics/InceptionScore
   /autoapi/synthval/metrics/FrechetDistance
   /autoapi/synthval/metrics/KernelDistance
   /autoapi/synthval/metrics/PRScores

.. autoapisummary::

   synthval.metrics.SimilarityMetric
   synthval.metrics.KLDivergenceEstimation
   synthval.metrics.WassersteinDistance
   synthval.metrics.EnergyDistance
   synthval.metrics.MeanMahalanobisDistance
   synthval.metrics.FCNNAccuracyMetric
   synthval.metrics.InceptionScore
   synthval.metrics.FrechetDistance
   synthval.metrics.KernelDistance
   synthval.metrics.PRScores