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Article | REF: AG455 V1

Numerical simulation and machine learning - Contribution of artificial intelligence to numerical modelling

Author: Jean-François SIGRIST

Publication date: January 10, 2024

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6. Glossary

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Principal Component Analysis (or PCA) is a method used in statistics to transform a set of correlated (e.g. linearly dependent) variables into a set of uncorrelated (e.g. linearly independent) variables: the "principal components" enable data to be analyzed along independent directions.

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