« Matrice mal conditionnée » : différence entre les versions


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== Définition ==
== Définition ==
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In mathematics, a condition number is a number representative of the change of an output proportionate to a change in the input of a function. For example, if a small change in the input results in a small change in the output, the function produces a small condition number and is said to be well-conditioned. Alternatively, if a small change in the input results in a large change in the output, the function produces a large condition number and is defined as ill-conditioned.
 
Imagine an example linear equation in which Ax = b. The condition number is, very generally, a representation of the rate at which the solution (x) changes with respect to changes in the value of (b). The condition number is a property of the matrix itself, not the algorithm. If the condition number of a matrix is too large, it is labeled as an ill-conditioned matrix. Condition numbers are representative of the accuracy of computing a matrix' inverse. For example, a well-conditioned matrix means its inverse can be computed with decent accuracy. Alternatively, an ill-conditioned matrix is not invertible and can have a condition number that is equal to infinity.


== Français ==
== Français ==
''' XXXXXXXXX '''
'''matrice mal conditionnée'''


== Anglais ==
== Anglais ==
''' Ill-conditioned Matrix'''
'''ill-conditioned matrix'''


In mathematics, a condition number is a number representative of the change of an output proportionate to a change in the input of a function. For example, if a small change in the input results in a small change in the output, the function produces a small condition number and is said to be well-conditioned. Alternatively, if a small change in the input results in a large change in the output, the function produces a large condition number and is defined as ill-conditioned.
Imagine an example linear equation in which Ax = b. The condition number is, very generally, a representation of the rate at which the solution (x) changes with respect to changes in the value of (b). The condition number is a property of the matrix itself, not the algorithm. If the condition number of a matrix is too large, it is labeled as an ill-conditioned matrix. Condition numbers are representative of the accuracy of computing a matrix' inverse. For example, a well-conditioned matrix means its inverse can be computed with decent accuracy. Alternatively, an ill-conditioned matrix is not invertible and can have a condition number that is equal to infinity.


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[https://deepai.org/machine-learning-glossary-and-terms/ill-conditioned-matrix    Source : DeepAI.org ]
[https://deepai.org/machine-learning-glossary-and-terms/ill-conditioned-matrix    Source : DeepAI.org ]


[[Catégorie:DeepAI.org]]
[[Catégorie:DeepAI.org]]
[[Catégorie:vocabulary]]
[[Catégorie:vocabulary]]

Version du 17 septembre 2021 à 10:28

en construction

Définition

In mathematics, a condition number is a number representative of the change of an output proportionate to a change in the input of a function. For example, if a small change in the input results in a small change in the output, the function produces a small condition number and is said to be well-conditioned. Alternatively, if a small change in the input results in a large change in the output, the function produces a large condition number and is defined as ill-conditioned.

Imagine an example linear equation in which Ax = b. The condition number is, very generally, a representation of the rate at which the solution (x) changes with respect to changes in the value of (b). The condition number is a property of the matrix itself, not the algorithm. If the condition number of a matrix is too large, it is labeled as an ill-conditioned matrix. Condition numbers are representative of the accuracy of computing a matrix' inverse. For example, a well-conditioned matrix means its inverse can be computed with decent accuracy. Alternatively, an ill-conditioned matrix is not invertible and can have a condition number that is equal to infinity.

Français

matrice mal conditionnée

Anglais

ill-conditioned matrix



Source : DeepAI.org