docs: update reference

src/cognitivefactory/interactive_clustering/__init__.py

@@ -8,6 +8,7 @@
 * Licence:      CeCILL (https://cecill.info/licences.fr.html)
 
 Three modules are available:
+
 - `constraints`: it provides a constraints manager, that stores annotated constraints on data and gives some feedback on information deduced (such as the transitivity between constraints or the situation of inconsistency). See [interactive_clustering/constraints](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/constraints/) documentation ;
 - `sampling`: it provides several constraints sampling algorithm, that selecte relevant contraints to annotate by an expert. See [interactive_clustering/sampling](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/sampling/) documentation ;
 - `clustering`: it provides several constrained clustering algorithms, that partition the data according to annotated constraints. See [interactive_clustering/clustering](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/clustering/) documentation ;

src/cognitivefactory/interactive_clustering/clustering/__init__.py

@@ -8,6 +8,7 @@
 * Licence:      CeCILL-C License v1.0 (https://cecill.info/licences.fr.html)
 
 This module provides several constrained clustering algorithms, that partition the data according to annotated constraints :
+
 - `abstract`: an abstract class that defines constrained clustering algorithms functionnalities. See [interactive_clustering/clustering/abstract](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/clustering/abstract/) documentation ;
 - `factory`: a factory to easily instantiate constrained clustering algorithm object. See [interactive_clustering/clustering/factory](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/clustering/factory/) documentation ;
 - `kmeans`: a constrained clustering algorithm implementation that uses COP-KMeans. See [interactive_clustering/clustering/kmeans](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/clustering/kmeans/) documentation ;

src/cognitivefactory/interactive_clustering/clustering/affinity_propagation.py

@@ -87,7 +87,7 @@ class AffinityPropagationConstrainedClustering(AbstractConstrainedClustering):
         print("Computed results", ":", dict_of_predicted_clusters)
         ```
 
-    Warnings:
+    Warns:
         FutureWarning: `clustering.affinity_propagation.AffinityPropagationConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
     """
 
@@ -109,7 +109,7 @@ def __init__(
             random_seed (Optional[int], optional): The random seed to use to redo the same clustering. Defaults to `None`.
             **kargs (dict): Other parameters that can be used in the instantiation.
 
-        Warnings:
+        Warns:
             FutureWarning: `clustering.affinity_propagation.AffinityPropagationConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
 
         Raises:

src/cognitivefactory/interactive_clustering/clustering/dbscan.py

@@ -88,7 +88,7 @@ class DBScanConstrainedClustering(AbstractConstrainedClustering):
         print("Computed results", ":", dict_of_predicted_clusters)
         ```
 
-    Warnings:
+    Warns:
         FutureWarning: `clustering.dbscan.DBScanConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
     """
 
@@ -111,7 +111,7 @@ def __init__(
             random_seed (Optional[int]): The random seed to use to redo the same clustering. Defaults to `None`.
             **kargs (dict): Other parameters that can be used in the instantiation.
 
-        Warnings:
+        Warns:
             FutureWarning: `clustering.dbscan.DBScanConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
 
         Raises:

src/cognitivefactory/interactive_clustering/clustering/factory.py

@@ -34,7 +34,7 @@ def clustering_factory(algorithm: str = "kmeans", **kargs) -> "AbstractConstrain
         algorithm (str): The identification of model to instantiate. Can be `"affinity_propagation"`, `"dbscan"`, `"hierarchical"`, `"kmeans"`, `"mpckmeans"` or `"spectral"`. Defaults to `"kmeans"`.
         **kargs (dict): Other parameters that can be used in the instantiation.
 
-    Warnings:
+    Warns:
         FutureWarning: `clustering.affinity_propagation.AffinityPropagationConstrainedClustering`, `clustering.dbscan.DBScanConstrainedClustering` and `clustering.mpckmeans.MPCKMeansConstrainedClustering` are still in development and are not fully tested : it is not ready for production use.
 
     Raises:

src/cognitivefactory/interactive_clustering/clustering/mpckmeans.py

@@ -85,7 +85,7 @@ class MPCKMeansConstrainedClustering(AbstractConstrainedClustering):
         print("Computed results", ":", dict_of_predicted_clusters)
         ```
 
-    Warnings:
+    Warns:
         FutureWarning: `clustering.mpckmeans.MPCKMeansConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
     """
 
@@ -110,7 +110,7 @@ def __init__(
             random_seed (Optional[int]): The random seed to use to redo the same clustering. Defaults to `None`.
             **kargs (dict): Other parameters that can be used in the instantiation.
 
-        Warnings:
+        Warns:
             FutureWarning: `clustering.mpckmeans.MPCKMeansConstrainedClustering` is still in development and is not fully tested : it is not ready for production use.
 
         Raises:

src/cognitivefactory/interactive_clustering/constraints/__init__.py

@@ -8,6 +8,7 @@
 * Licence:      CeCILL-C License v1.0 (https://cecill.info/licences.fr.html)
 
 This module provides a constraints manager, that stores annotated constraints on data and gives some feedback on information deduced (such as the transitivity between constraints or the situation of inconsistency) :
+
 - `abstract`: an abstract class that defines constraints managers functionnalities. See [interactive_clustering/constraints/abstract](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/constraints/abstract/) documentation ;
 - `factory`: a factory to easily instantiate constraints manager object. See [interactive_clustering/constraints/factory](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/constraints/factory/) documentation ;
 - `binary`: a constraints manager implementation that handles `MUST-LINK` and `CANNOT-LINK` constraints on pairs of data. See [interactive_clustering/constraints/binary](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/constraints/binary/) documentation ;

src/cognitivefactory/interactive_clustering/sampling/__init__.py

@@ -8,6 +8,7 @@
 * Licence:      CeCILL (https://cecill.info/licences.fr.html)
 
 This module provides several constraints sampling algorithm, that selecte relevant contraints to annotate by an expert :
+
 - `abstract`: an abstract class that defines constraints sampling algorithms functionnalities. See [interactive_clustering/sampling/abstract](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/sampling/abstract/) documentation ;
 - `factory`: a factory to easily instantiate constraints sampling algorithm object. See [interactive_clustering/sampling/factory](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/sampling/factory/) documentation ;
 - `clusters_based`: a constraints sampling algorithm implementation that uses constraints annotation, data similarity and clustering results. See [interactive_clustering/sampling/clusters_based](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/sampling/clusters_based/) documentation ;

src/cognitivefactory/interactive_clustering/utils/__init__.py

@@ -8,6 +8,7 @@
 * Licence:      CeCILL (https://cecill.info/licences.fr.html)
 
 This module provides several basic functionnalities, like data preprocessing and data vectorization :
+
 - `preprocessing`: a method to preprocess data. See [interactive_clustering/utils/preprocessing](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/utils/preprocessing/) documentation.
 - `vectorization`: a method to vectoize data. See [interactive_clustering/utils/vectorization](https://cognitivefactory.github.io/interactive-clustering/reference/cognitivefactory/interactive_clustering/utils/vectorization/) documentation.
 """