transforms elements of matrix into unscaled principal components.
Details and Options
- PrincipalComponents gives the principal component transform of matrix.
- The principal components of matrix are linear transformations of the original columns into uncorrelated columns arranged in order of decreasing variance.
- PrincipalComponents supports a Method option. The following explicit settings can be specified:
"Covariance" uses covariance method (default) "Correlation" uses correlation method
- If principal components of scaled columns (standardized principal components) are required, the option Method"Correlation" should be used.
- The dimensions of PrincipalComponents[matrix] are the same as the dimensions of matrix.
- If matrix consists of exact numbers or symbols, the result is also exact or symbolic, respectively.
Examplesopen allclose all
Properties & Relations (2)
The principal component columns are ordered by decreasing variance:
The mean of each principal component column is zero:
The principal component columns are not correlated:
The setting Method->"Correlation" yields the same results as standardizing the input matrix:
Wolfram Research (2010), PrincipalComponents, Wolfram Language function, https://reference.wolfram.com/language/ref/PrincipalComponents.html.
Wolfram Language. 2010. "PrincipalComponents." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/PrincipalComponents.html.
Wolfram Language. (2010). PrincipalComponents. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/PrincipalComponents.html