Incremental learning - Historique des versions

Pitpitt : Page redirigée vers Apprentissage incrémental

2019-12-08T21:13:57Z

Page redirigée vers Apprentissage incrémental

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+#REDIRECTION[[Apprentissage incrémental]]
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+[[Catégorie:ENGLISH]]
 [https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence   Source : Wikipedia]

Pitpitt : Redirection supprimée vers Algorithme d'apprentissage incrémental

2019-09-19T14:47:07Z

Redirection supprimée vers Algorithme d'apprentissage incrémental

← Version précédente		Version du 19 septembre 2019 à 10:47
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	~~#REDIRECTION~~[[~~Algorithme d~~'~~apprentissage incrémental]~~]
			== en construction ==
			[[Catégorie:Vocabulary]]
			[[Catégorie:Intelligence artificielle‏‎]]
			[[Catégorie:Wikipedia-IA‏‎ ]]

			== Définition ==
			...

			== Français ==
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			== Anglais ==
			''' Incremental learning '''

			is a method of machine learning, in which input data is continuously used to extend the existing model's knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms.

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			[https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence Source : Wikipedia]

Pitpitt : Page redirigée vers Algorithme d'apprentissage incrémental

2019-07-12T02:52:53Z

Page redirigée vers Algorithme d'apprentissage incrémental

← Version précédente		Version du 11 juillet 2019 à 22:52
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			#REDIRECTION[[Algorithme d'apprentissage incrémental]]
	~~== en construction ==~~

	[[~~Category:Vocabulary]]~~

	~~== Définition ==~~




	~~== Français ==~~





	~~== Anglais ==~~

	~~=== Incremental learning ===~~
	~~computer science, incremental learning is a method of machine learning, in which input data is continuously used to extend the existing model~~'s knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms.

	Many traditional machine learning algorithms inherently support incremental learning, other algorithms can be adapted to facilitate this. Examples of incremental algorithms include decisions trees (IDE4,[1] ID5R[2]), decision rules,[3] artificial neural networks (RBF networks,[4] Learn++,[5] Fuzzy ARTMAP,[6] TopoART,[7] ~~and IGNG[8]) or the incremental SVM.[9]~~

	The aim of incremental learning is for the learning model to adapt to new data without forgetting its existing knowledge, it does not retrain the model. Some incremental learners have built-in some parameter or assumption that controls the relevancy of old data, while others, called stable incremental machine learning algorithms, learn representations of the training data that are not even partially forgotten over time. Fuzzy ART[10] and TopoART[7] ~~are two examples for this second approach.~~

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Pitpitt : Remplacement de texte — « Entrez ici les domaines et catégories... » par «  »

2019-07-03T16:02:03Z

Remplacement de texte — « Entrez ici les domaines et catégories... » par «  »

← Version précédente		Version du 3 juillet 2019 à 12:02
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	== en construction ==		== en construction ==
	~~<small>Entrez ici les domaines et catégories...</small>~~
	[[Category:Vocabulary]]		[[Category:Vocabulary]]

Pitpitt : Remplacement de texte — « == Domaine == » par « == en construction == Entrez ici les domaines et catégories... »

2019-07-01T15:37:59Z

Remplacement de texte — « == Domaine == » par « == en construction == Entrez ici les domaines et catégories... »

← Version précédente		Version du 1 juillet 2019 à 11:37
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	== ~~Domaine~~ ==		== en construction ==
			<small>Entrez ici les domaines et catégories...</small>
	[[Category:Vocabulary]]		[[Category:Vocabulary]]

Pitpitt : Remplacement de texte — « Termes privilégiés » par « Français »

2018-12-31T19:42:19Z

Remplacement de texte — « Termes privilégiés » par « Français »

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	== ~~Termes privilégiés~~ ==		== Français ==

Pitpitt le 1 mars 2018 à 04:00

2018-03-01T04:00:57Z

← Version précédente		Version du 1 mars 2018 à 00:00
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	=== Incremental learning ===		=== Incremental learning ===
	computer science, incremental learning is a method of machine learning, in which input data is continuously used to extend the existing model's knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms.		computer science, incremental learning is a method of machine learning, in which input data is continuously used to extend the existing model's knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms.

	Many traditional machine learning algorithms inherently support incremental learning, other algorithms can be adapted to facilitate this. Examples of incremental algorithms include decisions trees (IDE4,[1] ID5R[2]), decision rules,[3] artificial neural networks (RBF networks,[4] Learn++,[5] Fuzzy ARTMAP,[6] TopoART,[7] and IGNG[8]) or the incremental SVM.[9]		Many traditional machine learning algorithms inherently support incremental learning, other algorithms can be adapted to facilitate this. Examples of incremental algorithms include decisions trees (IDE4,[1] ID5R[2]), decision rules,[3] artificial neural networks (RBF networks,[4] Learn++,[5] Fuzzy ARTMAP,[6] TopoART,[7] and IGNG[8]) or the incremental SVM.[9]

Pitpitt : Page créée avec « == Domaine == Category:Vocabulary == Définition == == Termes privilégiés == == Anglais == === Incremental learning === computer science, incremen... »

2018-03-01T02:46:35Z

Page créée avec « == Domaine == Category:Vocabulary == Définition == == Termes privilégiés == == Anglais == === Incremental learning === computer science, incremen... »

Nouvelle page

== Domaine ==
[[Category:Vocabulary]]

== Définition ==

== Termes privilégiés ==

== Anglais ==

=== Incremental learning ===
computer science, incremental learning is a method of machine learning, in which input data is continuously used to extend the existing model's knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms.

Many traditional machine learning algorithms inherently support incremental learning, other algorithms can be adapted to facilitate this. Examples of incremental algorithms include decisions trees (IDE4,[1] ID5R[2]), decision rules,[3] artificial neural networks (RBF networks,[4] Learn++,[5] Fuzzy ARTMAP,[6] TopoART,[7] and IGNG[8]) or the incremental SVM.[9]

The aim of incremental learning is for the learning model to adapt to new data without forgetting its existing knowledge, it does not retrain the model. Some incremental learners have built-in some parameter or assumption that controls the relevancy of old data, while others, called stable incremental machine learning algorithms, learn representations of the training data that are not even partially forgotten over time. Fuzzy ART[10] and TopoART[7] are two examples for this second approach.

Incremental learning - Historique des versions

Pitpitt : Page redirigée vers Apprentissage incrémental

Pitpitt : Redirection supprimée vers Algorithme d'apprentissage incrémental

Pitpitt : Page redirigée vers Algorithme d'apprentissage incrémental

Pitpitt : Remplacement de texte — « Entrez ici les domaines et catégories... » par « »

Pitpitt : Remplacement de texte — « == Domaine == » par « == en construction == Entrez ici les domaines et catégories... »

Pitpitt : Remplacement de texte — « Termes privilégiés » par « Français »