« Réduction de dimensionnalité » : différence entre les versions
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Version du 15 décembre 2020 à 19:07
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Feature reduction
Feature reduction, also known as dimensionality reduction, is the process of reducing the number of features in a resource heavy computation without losing important information. Reducing the number of features means the number of variables is reduced making the computer’s work easier and faster. Feature reduction can be divided into two processes: feature selection and feature extraction. There are many techniques by which feature reduction is accomplished. Some of the most popular are generalized discriminant analysis, autoencoders, non-negative matrix factorization, and principal component analysis.
Contributeurs: Claire Gorjux, Imane Meziani, wiki
