Concept information
Término preferido
backpropagation
Definición
- A gradient estimation technique used in supervised machine learning which consists in updating the weights of the neural network by iteratively propagating the error backward from the output layer to the input layer and then minimize the difference between the predicted and actual output. The backpropagation algorithm is used in image, speech, and pattern recognition as well as classification.
Concepto genérico
Etiquetas alternativas
- backprop
- backward propagation of errors
- BP
- error back propagation
- error feedback propagation
- feedback propagation
Nota
- The term back-propagation is often misunderstood as meaning the whole learning algorithm for multilayer neural networks. Backpropagation refers only to the method for computing the gradient, while other algorithms, such as stochastic gradient descent, is used to perform learning using this gradient. (Goodfellow et al., 6.5 Back-Propagation and Other Differentiation Algorithms, Deep Learning, 2016)
En otras lenguas
-
francés
-
rétropropagation d'erreur
-
rétropropagation d'erreurs
-
rétropropagation de l'erreur
-
rétropropagation des erreurs
URI
http://data.loterre.fr/ark:/67375/8LP-M7H9HK89-Z
{{label}}
{{#each values }} {{! loop through ConceptPropertyValue objects }}
{{#if prefLabel }}
{{/if}}
{{/each}}
{{#if notation }}{{ notation }} {{/if}}{{ prefLabel }}
{{#ifDifferentLabelLang lang }} ({{ lang }}){{/ifDifferentLabelLang}}
{{#if vocabName }}
{{ vocabName }}
{{/if}}