Methods

Summary

method	class parent	truncated documentation
__add__	Point	ajoute un vecteur a celui-ci
__eq__	Point	retourne True si les deux points self et a sont egaux, False sinon
__eq__	NeuralTreeNode
__getitem__	GraphDistance	returns a vertex or an edge if no vertex with the given index was found
__getitem__	NeuralTreeNet	Retrieves node and attributes for node i.
__getitem__	CompletionSystem	Returns elements[i].
__getstate__	NeuralTreeNode	usual
__iadd__	Point	ajoute un vecteur à celui-ci
__init__	Edge
__init__	GraphDistance	constructor
__init__	Vertex	constructor
__init__	_Edge
__init__	_Vertex
__init__	InformationPoint	constructeur, initialisation
__init__	LigneGradient	constructeur
__init__	SegmentNFA	segment + nombre de fausses alarmes
__init__	SegmentBord_Commun	constructeur, definit la definition de l’image
__init__	SegmentBord	initialise les dimensions et fait sorte que la classe contienne le premier segment
__init__	Point	constructeur
__init__	Segment	constructeur, pour éviter des erreurs d’etourderie, on crée des copies des extrémités a et b, comme ce sont …
__init__	NeuralTreeNode
__init__	NuagePoints	constructeur
__init__	NuagePointsLaesa	Construit la classe
__init__	MlGridBenchMark
__init__	BaseNeuralTreeNet
__init__	NeuralTreeNet
__init__	NeuralTreeNetClassifier
__init__	NeuralTreeNetRegressor
__init__	ROC	Initialisation with a dataframe and two or three columns:
__init__	CompletionTrieNode
__init__	CompletionElement	constructor
__init__	CompletionSystem	fill the completion system
__init__	BaseOptimizer
__init__	SGDOptimizer
__iter__	CompletionTrieNode	Iterates on all nodes (sorted).
__iter__	CompletionSystem	Iterates over elements.
__len__	LigneGradient	Retourne le nombre de pixels dans le segment, peut etre different de la liste self.info_ligne, self.nb …
__len__	NeuralTreeNet	Returns the number of nodes
__len__	ROC	usual
__len__	CompletionSystem	Number of elements.
__lt__	SegmentNFA
__repr__	Edge	usual
__repr__	GraphDistance	usual
__repr__	Vertex	usual
__repr__	Point	usuel
__repr__	NeuralTreeNode	usual
__repr__	NeuralTreeNet	usual
__repr__	ROC	Shows first elements, precision rate.
__repr__	CompletionElement	usual
__setstate__	NeuralTreeNode	usual
__str__	Edge	usual
__str__	GraphDistance	usual
__str__	Vertex	usual
__str__	InformationPoint	permet d’afficher cette classe
__str__	SegmentNFA	permet d’afficher ce segment
__str__	SegmentBord_Commun	permet d’afficher le segment
__str__	SegmentBord	permet d’afficher le segment
__str__	Point	permet d’afficher un point avec l’instruction print
__str__	Segment	permet d’afficher le segment avec l’instruction print
__str__	ROC	Shows first elements, precision rate.
__str__	CompletionTrieNode	usual
__sub__	Point	soustraction de deux de vecteurs
_add	CompletionTrieNode	Adds a child.
_common_loss_dloss	NeuralTreeNode	Common beginning to methods loss, dlossds, dlossdw.
_common_loss_dloss	NeuralTreeNet	Common beginning to methods loss, dlossds, dlossdw.
_display_progress	BaseOptimizer	Displays training progress.
_display_progress	SGDOptimizer	Displays training progress.
_evaluate_early_stopping	BaseOptimizer
_evaluate_early_stopping	SGDOptimizer
_get_output_node_attr	NeuralTreeNet	Retrieves the output nodes. nb_last is the number of expected outputs.
_get_updates	BaseOptimizer
_get_updates	SGDOptimizer	Gets the values used to update params with given gradients.
_predict	NeuralTreeNode	Computes inputs of the activation function.
_predict_one	NeuralTreeNet
_private__init__	GraphDistance
_private_string_path_matching	GraphDistance
_regularize_gradient	BaseOptimizer	Applies regularization.
_regularize_gradient	SGDOptimizer	Applies regularization.
_set_fcts	NeuralTreeNode
_update_members	NeuralTreeNet	Updates internal members.
all_completions	CompletionTrieNode	Retrieves all completions for a node, the method does not need precompute_stat() to be run first.
all_mks_completions	CompletionTrieNode	Retrieves all completions for a node, the method assumes precompute_stat() was run.
angle	Point	retourne l’angle du vecteur
append	NeuralTreeNet	Appends a node into the graph.
arrondi	Point	retourne les coordonnées arrondies à l’entier le plus proche
as_array	Point	Convertit en array.
auc	ROC	Computes the area under the curve (:epkg:`AUC`).
auc_interval	ROC	Determines a confidence interval for the :epkg:`AUC` with bootstrap.
bench_experiment	MlGridBenchMark	Calls meth fit.
calcul_bord2	SegmentBord	calcule précisément la second extrémité, parcourt la demi-droite jusqu’à sortir de l’image, le dernier point est …
calcul_vecteur	SegmentBord	En fonction de l’angle, calcule le vecteur direction du segment, ensuite fixe la première extrémité du segment self.a …
calcul_vecteur_fin	SegmentBord	propose une seconde extrémité connaissant la première, beaucoup plus loin en conservant la meme orientation, …
calcule_NFA	LigneGradient	ext[ij[0]]: premier indice du segment, ext[ij[1]]: dernier indice du segment, calcule le nombre …
clean_dead_ends	GraphDistance
clear	NeuralTreeNet	Clear all nodes
common_paths	GraphDistance
compare_with_trie	CompletionSystem	Compares the results with the other implementation.
compute_metrics	CompletionSystem	Computes the metric for the completion itself.
compute_predecessor	GraphDistance	usual
compute_roc_curve	ROC	Computes a ROC curve with nb points avec nb, if nb == -1, there are as many as points as the data contains, …
compute_successor	GraphDistance
confusion	ROC	Computes the confusion matrix for a specific score or all if score is None.
connect_root_and_leave	GraphDistance
copy	SegmentBord_Commun	Copie l’instance.
copy	NeuralTreeNet
decision_function	BaseNeuralTreeNet	Returns the classification probabilities.
decision_function	NeuralTreeNetClassifier	Returns the classification probabilities.
decision_function	NeuralTreeNetRegressor	Returns the classification probabilities.
decoupe_gradient	SegmentBord_Commun	Pour un segment donne joignant deux bords de l’image, cette fonction récupère le gradient et construit une liste …
directeur	SegmentBord	retourne une copie du vecteur directeur
directeur	Segment	retourne le vecteur directeur du segment, ce vecteur est norme
distance	NuagePoints	Retourne une distance entre deux éléments.
distance_matching_graphs_paths	GraphDistance	Computes an alignment between two graphs.
dlossds	_TrainingAPI	Computes the loss derivative due to prediction error.
dlossds	NeuralTreeNode	Computes the loss derivative due to prediction error.
dlossds	NeuralTreeNet	Computes the loss derivative against the inputs.
draw_vertices_edges	GraphDistance
edit_distance_path	GraphDistance	Tries to align two paths from two graphs.
end	MlGridBenchMark	nothing to do
enumerate_all_paths	GraphDistance
enumerate_test_metric	CompletionSystem	Evaluates the completion set on a set of queries, the function returns a list of CompletionElement …
extremite	LigneGradient	Comptabilise les indices des extremites possibles, les pixels choisis ont un gradient de la bonne orientation.
fill_cache	_TrainingAPI	Creates a cache with intermediate results.
fill_cache	NeuralTreeNode	Creates a cache with intermediate results. lX is the results before the activation function, aX …
fill_cache	NeuralTreeNet	Creates a cache with intermediate results.
find	CompletionTrieNode	Returns the node which holds all completions starting with a given prefix.
find	CompletionSystem	Not very efficient, finds an item in a the list.
first	Segment	Retourne la première extrémité.
fit	_TrainingAPI	Fits a neuron.
fit	NuagePoints	Follows sklearn API.
fit	NuagePointsLaesa	Follows sklearn API.
fit	MlGridBenchMark	Trains a model.
fit	BaseNeuralTreeNet	Trains the estimator.
fit	NeuralTreeNetClassifier	Trains the estimator.
fit	NeuralTreeNetRegressor	Trains the estimator.
get_matching_functions	GraphDistance	returns default matching functions between two vertices and two edges
get_order_vertices	GraphDistance
gradient	_TrainingAPI	Computes the gradient in X knowing the expected value y.
gradient_backward	_TrainingAPI	Computes the gradient in X.
gradient_backward	NeuralTreeNode	Computes the gradients at point X.
gradient_backward	NeuralTreeNet	Computes the gradient in X.
graphs	MlGridBenchMark	Plots multiples graphs.
has_aligned_point	LigneGradient	Dit s’il existe des points alignés sur le segment.
init_metrics	CompletionElement	initiate the metrics
is_edge	Edge	returns True
is_edge	Vertex	returns False
is_vertex	Edge	returns False
is_vertex	Vertex	returns True
items	CompletionTrieNode	Iterates on children, iterates on weight, key, child.
items	CompletionSystem	Iterates on (e.value, e).
items_list	CompletionTrieNode	All children nodes inluding itself in a list.
iter_leaves	CompletionTrieNode	Iterators on leaves sorted per weight, yield weight, value.
iteration_ends	BaseOptimizer	Performs update to learning rate and potentially other states at the end of an iteration.
iteration_ends	SGDOptimizer	Performs updates to learning rate and potential other states at the end of an iteration.
kneighbors	NuagePoints	Return the k nearest neighbors.
label	NuagePoints	Retourne le label de l’object d’indice i.
last	Segment	Retourne la seconde extrémité.
leaves	CompletionTrieNode	Iterators on leaves.
loss	_TrainingAPI	Computes the loss. Returns a float.
loss	NeuralTreeNode	Computes the loss. Returns a float.
loss	NeuralTreeNet	Computes the loss due to prediction error. Returns a float.
loss_regularization	BaseOptimizer
loss_regularization	SGDOptimizer
milieu	SegmentBord	Un autre segment, pour débugger le programme, choisit une orientation pour laquelle on sait que le résultat …
min_dynamic_keystroke	CompletionTrieNode	Returns the dynamic minimum keystrokes for a word.
min_dynamic_keystroke2	CompletionTrieNode	Returns the modified dynamic minimum keystrokes for a word.
min_keystroke	CompletionTrieNode	Returns the minimum keystrokes for a word without optimisation, this function should be used if you only have a …
min_keystroke0	CompletionTrieNode	Returns the minimum keystrokes for a word.
next	SegmentBord	passe au segment suivant dans le parcours de l’image
next_chemin	LigneGradient	Retourne le couple suivant d’extrémités possibles, None, dans le cas contraire.
normal	Segment	retourne le vecteur normal du segment, ce vecteur est norme
normalise	Point	normalise le vecteur, sa norme devient 1
norme	Point	Retourne la norme.
plot	ROC	Plots a ROC curve.
plot_graphs	MlGridBenchMark	Plots all graphs in the same graphs.
ppv	NuagePoints	Retourne l’élément le plus proche de obj et sa distance avec obj.
ppv	NuagePointsLaesa	Retourne l’élément le plus proche de obj et sa distance avec obj, utilise la sélection à l’aide pivots
precision	ROC	Computes the precision.
precompute_stat	CompletionTrieNode	Computes and stores list of completions for each node, computes mks.
predict	NeuralTreeNode	Computes neuron outputs.
predict	NeuralTreeNet
predict	NeuralTreeNetClassifier	Returns the predicted classes.
predict	NeuralTreeNetRegressor	Returns the predicted classes.
predict_proba	NeuralTreeNetClassifier	Returns the classification probabilities.
predict_score_experiment	MlGridBenchMark	Calls method score.
premier	SegmentBord	définit le premier segment, horizontal, part du bord gauche
premier_chemin	LigneGradient	Retourne la premiere d’extremite possible.
preprocess_dataset	MlGridBenchMark	Splits the dataset into train and test.
private_count_left_right	GraphDistance
private_kruskal_matrix	GraphDistance
random_cloud	ROC	Resamples among the data.
roc_intersect	ROC	The ROC curve is defined by a set of points. This function interpolates those points to determine …
roc_intersect_interval	ROC	Computes a confidence interval for the value returned by roc_intersect().
scalaire	Point	Calcule le produit scalaire.
scalairek	Point	Mulitplication par un scalaire.
score	MlGridBenchMark	Scores a model.
segments_significatifs	LigneGradient	Comptabilise le nombre de segments significatifs sur une ligne et les mémorise.
selection_pivots	NuagePointsLaesa	Sélectionne nb pivots aléatoirements.
sort_values	CompletionSystem	sort the elements by value
sort_weight	CompletionSystem	Sorts the elements by value.
str_all_completions	CompletionTrieNode	Builds a string with all completions for all prefixes along the paths.
str_all_completions	CompletionElement	builds a string with all completions for all prefixes along the paths, this is only available if parameter …
str_mks	CompletionElement	return a string with metric information
str_mks0	CompletionElement	return a string with metric information
test_metric	CompletionSystem	Evaluates the completion set on a set of queries, the function returns a dictionary with the aggregated metrics …
to_dict	CompletionSystem	Returns a dictionary.
to_dot	NeuralTreeNet	Exports the neural network into dot.
train	BaseOptimizer	Optimizes the coefficients.
train	SGDOptimizer	Optimizes the coefficients.
tuples	CompletionSystem	Iterates on (e.weight, e.value).
unsorted_iter	CompletionTrieNode	Iterates on all nodes.
update_coef	BaseOptimizer	Updates coefficients with given gradient.
update_coef	SGDOptimizer	Updates coefficients with given gradient.
update_metrics	CompletionElement	update the metrics
update_stat_dynamic	CompletionTrieNode	Must be called after precompute_stat() and computes dynamic mks (see Dynamic Minimum Keystroke). …
update_training_weights	_TrainingAPI	Updates weights.
update_training_weights	NeuralTreeNode	Updates weights.
update_training_weights	NeuralTreeNet	Updates weights.