.. _l-classes:

Classes
=======

.. contents::
    :local:
    :depth: 1


Summary
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| class                                                                                                    | class parent | truncated documentation                                                                                                      |
+==========================================================================================================+==============+==============================================================================================================================+
| :class:`BaseNeuralTreeNet <mlstatpy.ml.neural_tree.BaseNeuralTreeNet>`                                   |              | Classifier or regressor following :epkg:`scikit-learn` API.                                                                  |
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| :class:`BaseOptimizer <mlstatpy.optim.sgd.BaseOptimizer>`                                                |              | Base stochastic gradient descent optimizer.                                                                                  |
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| :class:`CompletionElement <mlstatpy.nlp.completion_simple.CompletionElement>`                            |              | Definition of an element in a completion system, it contains the following members:                                          |
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| :class:`CompletionSystem <mlstatpy.nlp.completion_simple.CompletionSystem>`                              |              | define a completion system                                                                                                   |
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| :class:`CompletionTrieNode <mlstatpy.nlp.completion.CompletionTrieNode>`                                 |              | Node definition in a trie used to do completion, see :ref:`l-completion0`. This implementation is not very efficient ...     |
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| :class:`DataException <mlstatpy.data.data_exceptions.DataException>`                                     |              | raised when retrieving data                                                                                                  |
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| :class:`Edge <mlstatpy.graph.graph_distance.Edge>`                                                       |              | Defines an edge of a graph.                                                                                                  |
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| :class:`GraphDistance <mlstatpy.graph.graph_distance.GraphDistance>`                                     |              | Defines a graph to compute a distance between two graphs.                                                                    |
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| :class:`InformationPoint <mlstatpy.image.detection_segment.detection_nfa.InformationPoint>`              |              | Pour retenir toutes les informations relatives a un segment, une position (pos), la norme du gradient (norme), ...           |
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| :class:`LigneGradient <mlstatpy.image.detection_segment.detection_nfa.LigneGradient>`                    |              | Stocke toutes les informations relatives à un segment de l'image reliant deux points du contour, reçoit les informations ... |
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| :class:`MlGridBenchMark <mlstatpy.ml.ml_grid_benchmark.MlGridBenchMark>`                                 |              | The class tests a list of model over a list of datasets.                                                                     |
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| :class:`NeuralTreeNet <mlstatpy.ml.neural_tree.NeuralTreeNet>`                                           |              | Node ensemble.                                                                                                               |
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| :class:`NeuralTreeNetClassifier <mlstatpy.ml.neural_tree.NeuralTreeNetClassifier>`                       |              | Classifier following :epkg:`scikit-learn` API.                                                                               |
+----------------------------------------------------------------------------------------------------------+--------------+------------------------------------------------------------------------------------------------------------------------------+
| :class:`NeuralTreeNetRegressor <mlstatpy.ml.neural_tree.NeuralTreeNetRegressor>`                         |              | Regressor following :epkg:`scikit-learn` API.                                                                                |
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| :class:`NeuralTreeNode <mlstatpy.ml._neural_tree_node.NeuralTreeNode>`                                   |              | One node in a neural network.                                                                                                |
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| :class:`NuagePoints <mlstatpy.ml.kppv.NuagePoints>`                                                      |              | Définit une classe de nuage de points. On suppose qu'ils sont définis par une matrice, chaque ligne est un élément. ...      |
+----------------------------------------------------------------------------------------------------------+--------------+------------------------------------------------------------------------------------------------------------------------------+
| :class:`NuagePointsLaesa <mlstatpy.ml.kppv_laesa.NuagePointsLaesa>`                                      |              | Implémente l'algorithme des plus proches voisins, version :ref:`LAESA <space_metric_algo_laesa_prime>`_                      |
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| :class:`Point <mlstatpy.image.detection_segment.geometrie.Point>`                                        |              | Définit un point de l'image ou un vecteur, deux coordonnées *x* et *y* qui sont réelles.                                     |
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| :class:`ROC <mlstatpy.ml.roc.ROC>`                                                                       |              | Helper to draw a :epkg:`ROC` curve.                                                                                          |
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| :class:`SGDOptimizer <mlstatpy.optim.sgd.SGDOptimizer>`                                                  |              | Stochastic gradient descent optimizer with momentum.                                                                         |
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| :class:`Segment <mlstatpy.image.detection_segment.geometrie.Segment>`                                    |              | Définit un segment, soit deux :class:`Point`.                                                                                |
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| :class:`SegmentBord <mlstatpy.image.detection_segment.detection_segment_segangle.SegmentBord>`           |              | Définit un segment allant d'un bord à un autre de l'image, la classe va balayer toutes les orientations possibles, ...       |
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| :class:`SegmentBord_Commun <mlstatpy.image.detection_segment.detection_segment_bord.SegmentBord_Commun>` |              | Définit un segment allant d'un bord a un autre de l'image, la méthode importante est :meth:`decoupe_gradient`. ...           |
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| :class:`SegmentNFA <mlstatpy.image.detection_segment.detection_nfa.SegmentNFA>`                          |              | Un segment + un nombre de fausses alarmes, servira a memoriser les segments significatifs.                                   |
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| :class:`Vertex <mlstatpy.graph.graph_distance.Vertex>`                                                   |              | Defines a vertex of a graph.                                                                                                 |
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| :class:`VoronoiEstimationError <mlstatpy.ml.voronoi.VoronoiEstimationError>`                             |              | Raised when the algorithm failed.                                                                                            |
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| :class:`_Edge <mlstatpy.graph.graph_distance._Edge>`                                                     |              |                                                                                                                              |
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| :class:`_TrainingAPI <mlstatpy.ml._neural_tree_api._TrainingAPI>`                                        |              | Declaration of function needed to train a model.                                                                             |
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| :class:`_Vertex <mlstatpy.graph.graph_distance._Vertex>`                                                 |              |                                                                                                                              |
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