.. _l-staticmethods:

Static Methods
==============

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


Summary
+++++++

+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| staticmethod                                                                                                             | class parent       | truncated documentation                                                                                         |
+==========================================================================================================================+====================+=================================================================================================================+
| :py:meth:`_create_from_tree_compact <mlstatpy.ml.neural_tree.NeuralTreeNet._create_from_tree_compact>`                   | NeuralTreeNet      | Implements strategy one. See @see meth create_from_tree.                                                        |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_create_from_tree_one <mlstatpy.ml.neural_tree.NeuralTreeNet._create_from_tree_one>`                           | NeuralTreeNet      | Implements strategy one. See @see meth create_from_tree.                                                        |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_dleakyrelu <mlstatpy.ml._neural_tree_node.NeuralTreeNode._dleakyrelu>`                                        | NeuralTreeNode     | Derivative of the Leaky Relu function.                                                                          |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_drelu <mlstatpy.ml._neural_tree_node.NeuralTreeNode._drelu>`                                                  | NeuralTreeNode     | Derivative of the Relu function.                                                                                |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_dsigmoid <mlstatpy.ml._neural_tree_node.NeuralTreeNode._dsigmoid>`                                            | NeuralTreeNode     | Derivativ of the sigmoid function.                                                                              |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_dsoftmax <mlstatpy.ml._neural_tree_node.NeuralTreeNode._dsoftmax>`                                            | NeuralTreeNode     | Derivative of the softmax function.                                                                             |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_leakyrelu <mlstatpy.ml._neural_tree_node.NeuralTreeNode._leakyrelu>`                                          | NeuralTreeNode     | Leaky Relu function.                                                                                            |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_relu <mlstatpy.ml._neural_tree_node.NeuralTreeNode._relu>`                                                    | NeuralTreeNode     | Relu function.                                                                                                  |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :py:meth:`_softmax <mlstatpy.ml._neural_tree_node.NeuralTreeNode._softmax>`                                              | NeuralTreeNode     | Derivative of the softmax function.                                                                             |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`build <mlstatpy.nlp.completion.CompletionTrieNode.build>`                                                         | CompletionTrieNode | Builds a trie.                                                                                                  |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`create_from_tree <mlstatpy.ml.neural_tree.NeuralTreeNet.create_from_tree>`                                        | NeuralTreeNet      | Creates a :class:`NeuralTreeNet` instance from a :epkg:`DecisionTreeClassifier`                                 |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`empty_prefix <mlstatpy.nlp.completion_simple.CompletionElement.empty_prefix>`                                     | CompletionElement  | return an instance filled with an empty prefix                                                                  |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`get_activation_dloss_function <mlstatpy.ml._neural_tree_node.NeuralTreeNode.get_activation_dloss_function>`       | NeuralTreeNode     | Returns the derivative of the default loss function based on the activation function. It returns a function ... |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`get_activation_function <mlstatpy.ml._neural_tree_node.NeuralTreeNode.get_activation_function>`                   | NeuralTreeNode     | Returns the activation function. It returns a function *y=f(x)*.                                                |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`get_activation_gradient_function <mlstatpy.ml._neural_tree_node.NeuralTreeNode.get_activation_gradient_function>` | NeuralTreeNode     | Returns the activation function. It returns a function *y=f'(x)*. About the sigmoid:                            |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`get_activation_loss_function <mlstatpy.ml._neural_tree_node.NeuralTreeNode.get_activation_loss_function>`         | NeuralTreeNode     | Returns a default loss function based on the activation function. It returns two functions *g=loss(x,y)*.       |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`get_list_of_vertices <mlstatpy.graph.graph_distance.GraphDistance.get_list_of_vertices>`                          | GraphDistance      |                                                                                                                 |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+
| :meth:`load_from_file <mlstatpy.graph.graph_distance.GraphDistance.load_from_file>`                                      | GraphDistance      | loads a graph from a file                                                                                       |
+--------------------------------------------------------------------------------------------------------------------------+--------------------+-----------------------------------------------------------------------------------------------------------------+