« Erreur vraisemblable » : différence entre les versions


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   '''Definition:'''
   '''Definition:'''
An inlier is a data value that lies in the interior of a statistical distribution and is in error. Because inliers are difficult to distinguish from good data values they are sometimes difficult to find and correct.
An inlier is a data value that lies in the interior of a statistical distribution and is in error. Because inliers are difficult to distinguish from good data values they are sometimes difficult to find and correct.
 
  '''Context:'''
  '''Context:'''
  A simple example of an inlier might be a value in a record reported in the wrong units, say degrees Fahrenheit instead of degrees Celsius.
  A simple example of an inlier might be a value in a record reported in the wrong units, say degrees Fahrenheit instead of degrees Celsius.
  '''Source Publication:'''
  '''Source Publication:'''
  Economic Commission for Europe of the United Nations (UNECE), "Glossary of Terms on Statistical Data  
  Economic Commission for Europe of the United Nations (UNECE), "Glossary of Terms on Statistical Data  

Version du 5 janvier 2021 à 22:59

en construction

Définition

Une inlier est une observation de données qui se trouve dans le reste de l’ensemble de données et qui est inhabituelle ou une erreur. Puisqu’elle se situe dans l’ensemble de données, elle est généralement plus difficile à identifier qu’une observation aberrante et nécessite des données externes pour les identifier.

Français

Une inlier

Anglais

An inlier


 Definition:
An inlier is a data value that lies in the interior of a statistical distribution and is in error. Because inliers are difficult to distinguish from good data values they are sometimes difficult to find and correct.
Context:
A simple example of an inlier might be a value in a record reported in the wrong units, say degrees Fahrenheit instead of degrees Celsius.
Source Publication:
Economic Commission for Europe of the United Nations (UNECE), "Glossary of Terms on Statistical Data 
Editing", Conference of European Statisticians Methodological material, Geneva, 2000.

Cross References: Outlier

Source : towardsdatascience



Contributeurs: Imane Meziani, wiki, Sihem Kouache