« Imputation » : différence entre les versions
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''' Imputation''' | ''' Imputation''' | ||
''' Data Imputation''' | |||
In essence, imputation is simply replacing missing data with substituted values. Often, these values are simply taken from a random distribution to avoid bias. | In essence, imputation is simply replacing missing data with substituted values. Often, these values are simply taken from a random distribution to avoid bias. | ||
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[https://deepai.org/machine-learning-glossary-and-terms/Imputation Source : DeepAI.org ] | [https://deepai.org/machine-learning-glossary-and-terms/Imputation Source : DeepAI.org ] | ||
https://www.kdnuggets.com/2020/12/20-core-data-science-concepts-beginners.html | |||
[[Catégorie:DeepAI.org]] | [[Catégorie:DeepAI.org]] | ||
Version du 6 janvier 2021 à 23:54
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Définition
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Anglais
Imputation
Data Imputation
In essence, imputation is simply replacing missing data with substituted values. Often, these values are simply taken from a random distribution to avoid bias.
Imputation is a fairly new field and because of this, many researchers are testing the methods to make imputation the most useful. Currently, the methods we have to implement imputation aren’t as effective as researchers believe they could be, and involve introducing bias or by decreasing the representative power of the results.
https://www.kdnuggets.com/2020/12/20-core-data-science-concepts-beginners.html
Contributeurs: Imane Meziani, Jean Benoît Morel, wiki
