« Régression Lasso » : différence entre les versions

Version du 9 novembre 2021 à 16:04

régression Lasso

Lasso regression

Source : DeepAI.org

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-==en construction==
+== Définition ==
-== Définition ==
-XXXXXXXXX
 == Français ==
-''' XXXXXXXXX '''
+'''régression Lasso'''
 == Anglais ==
-''' Lasso Regression'''
+'''Lasso regression'''
-Lasso regression for neural networks performs regularization during the training phase with the L1 norm, i.e. it adds a term which is the sum of the absolute values of the weights to the objective (loss) function being minimized. Thus, lasso regression minimizes the following during training: Objective = base_loss(weights) + alpha * (sum of absolute value of the weights). The base_loss will depend on the underling task (e.g. cross-entropy loss for classification) and alpha is generally adjusted during model validation, and is called the regularization parameter. Lasso stands for "least absolute shrinkage and selection operator."
 <small>
+[https://deepai.org/machine-learning-glossary-and-terms/lasso-regression   Source : DeepAI.org ]
+[http://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/fr_Tanagra_Regression_Lasso_Python.pdf   Source : Université Lyon 2 ]
-[https://deepai.org/machine-learning-glossary-and-terms/lasso-regression   Source : DeepAI.org ]
+[https://www.xlstat.com/fr/solutions/fonctionnalites/regression-lasso   Source : XLSTAT ]
 [[Catégorie:DeepAI.org]]
 [[Catégorie:vocabulary]]