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.


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Basic Examples  (1)

Principal components of two datasets:

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Scope  (3)

Options  (1)

Properties & Relations  (2)

Possible Issues  (1)

Neat Examples  (1)

See Also

Eigenvectors  Standardize  KarhunenLoeveDecomposition  SingularValueDecomposition  SingularValueList  DimensionReduce

Introduced in 2010