..
   Copyright 2021 IRT Saint-Exupéry, https://www.irt-saintexupery.com

   This work is licensed under the Creative Commons Attribution-ShareAlike 4.0
   International License. To view a copy of this license, visit
   http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative
   Commons, PO Box 1866, Mountain View, CA 94042, USA.

.. _gen_ml_quality_algos:

Quality measures
================

.. warning::
   Some capabilities may require the :ref:`installation <installation>` of |g| with :ref:`all its features <dependencies>`
   and some others may depend on :ref:`plugins <plugins>`.

.. note::
   All the features of the wrapped libraries may not be exposed through |g|.



.. raw:: html

    <style>
    th {
      cursor: pointer;
    }

    th, td {
      text-align: center;
    }

    tr:hover {
        border: 1px solid black;
    }

    tr:nth-child(even) {
      background-color: #f2f2f2
    }
    </style>

    <script>
    function sortTable(n) {
      var table, rows, switching, i, x, y, shouldSwitch, dir, switchcount = 0;
      table = document.getElementById("myTable");
      switching = true;
      dir = "asc";
      while (switching) {
        switching = false;
        rows = table.rows;
        for (i = 1; i < (rows.length - 1); i++) {
          shouldSwitch = false;
          x = rows[i].getElementsByTagName("TD")[n];
          y = rows[i + 1].getElementsByTagName("TD")[n];
          if (dir == "asc") {
            if (x.innerHTML.toLowerCase() > y.innerHTML.toLowerCase()) {
              shouldSwitch= true;
              break;
            }
          } else if (dir == "desc") {
            if (x.innerHTML.toLowerCase() < y.innerHTML.toLowerCase()) {
              shouldSwitch = true;
              break;
            }
          }
        }
        if (shouldSwitch) {
          rows[i].parentNode.insertBefore(rows[i + 1], rows[i]);
          switching = true;
          switchcount ++;
        } else {
          if (switchcount == 0 && dir == "asc") {
            dir = "desc";
            switching = true;
          }
        }
      }
    }
    </script>



.. _F1Measure_options:

F1Measure
---------



Module: :class:`gemseo.mlearning.quality_measures.f1_measure`





.. raw:: html

    <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
    <link rel="stylesheet" href="../_static/css/gemseo.css" type="text/css" />
























    <dl class="field-list simple">
    <dt class="field-odd">Required parameters</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**algo** : *BaseMLClassificationAlgo*

A machine learning algorithm for classification.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



    <dl class="field-list simple">
    <dt class="field-odd">Optional parameters</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**fit_transformers** : *bool, optional*

Whether to re-fit the transformers
when using resampling techniques.
If ``False``,
use the transformers of the algorithm fitted
from the whole learning dataset.


By default it is set to True.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _MSEMeasure_options:

MSEMeasure
----------



Module: :class:`gemseo.mlearning.quality_measures.mse_measure`





.. raw:: html

    <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
    <link rel="stylesheet" href="../_static/css/gemseo.css" type="text/css" />
























    <dl class="field-list simple">
    <dt class="field-odd">Required parameters</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**algo** : *BaseMLRegressionAlgo*

A machine learning algorithm for regression.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



    <dl class="field-list simple">
    <dt class="field-odd">Optional parameters</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**fit_transformers** : *bool, optional*

Whether to re-fit the transformers
when using resampling techniques.
If ``False``,
use the transformers of the algorithm fitted
from the whole learning dataset.


By default it is set to True.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _R2Measure_options:

R2Measure
---------



Module: :class:`gemseo.mlearning.quality_measures.r2_measure`





.. raw:: html

    <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
    <link rel="stylesheet" href="../_static/css/gemseo.css" type="text/css" />
























    <dl class="field-list simple">
    <dt class="field-odd">Required parameters</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**algo** : *BaseMLRegressionAlgo*

A machine learning algorithm for regression.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



    <dl class="field-list simple">
    <dt class="field-odd">Optional parameters</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**fit_transformers** : *bool, optional*

Whether to re-fit the transformers
when using resampling techniques.
If ``False``,
use the transformers of the algorithm fitted
from the whole learning dataset.


By default it is set to True.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _RMSEMeasure_options:

RMSEMeasure
-----------



Module: :class:`gemseo.mlearning.quality_measures.rmse_measure`





.. raw:: html

    <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
    <link rel="stylesheet" href="../_static/css/gemseo.css" type="text/css" />
























    <dl class="field-list simple">
    <dt class="field-odd">Required parameters</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**algo** : *BaseMLRegressionAlgo*

A machine learning algorithm for regression.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



    <dl class="field-list simple">
    <dt class="field-odd">Optional parameters</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**fit_transformers** : *bool, optional*

Whether to re-fit the transformers
when using resampling techniques.
If ``False``,
use the transformers of the algorithm fitted
from the whole learning dataset.


By default it is set to True.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



.. _SilhouetteMeasure_options:

SilhouetteMeasure
-----------------



Module: :class:`gemseo.mlearning.quality_measures.silhouette_measure`





.. raw:: html

    <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
    <link rel="stylesheet" href="../_static/css/gemseo.css" type="text/css" />
























    <dl class="field-list simple">
    <dt class="field-odd">Required parameters</dt>
    <dd class="field-odd"><ul class="simple">

    <li>

**algo** : *BaseMLPredictiveClusteringAlgo*

A clustering algorithm.

.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>



    <dl class="field-list simple">
    <dt class="field-odd">Optional parameters</dt>
    <dd class="field-odd"><ul class="simple">


    <li>

**fit_transformers** : *bool, optional*

Whether to re-fit the transformers
when using resampling techniques.
If ``False``,
use the transformers of the algorithm fitted
from the whole learning dataset.


By default it is set to True.


.. raw:: html

    </li>

    </ul>
    </dd>
    </dl>