2. Principal component analysis (PCA)
2.1 Objectives
The purpose of principal component analysis is to study data resulting from the observation of p quantitative variables on n individuals, arranged in a matrix X (n x p). The objectives are :
the "optimal" graphical representation of the individuals (lines), minimizing the distortions of the point cloud, in a subspace E q of dimension q (q < p) of the vector space ;
the graphical representation of variables in a subspace F q of the vector space...
Exclusive to subscribers. 97% yet to be discovered!
Already subscribed? Log in!
Principal component analysis (PCA)
Other factorial methods
Article included in this offer
"Mathematics"
(
167 articles
)
Updated and enriched with articles validated by our scientific committees
A set of exclusive tools to complement the resources
Bibliography
Exclusive to subscribers. 97% yet to be discovered!
Already subscribed? Log in!
