Wolfram Language & System 10.4 (2016)|Legacy Documentation

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projects the vectors onto an approximating manifold in lower-dimensional space.

projects onto an approximating manifold in n-dimensional space.

Details and OptionsDetails and Options

  • The vectors must be numerical and must all be of the same length.
  • DimensionReduce[vecs] automatically chooses an appropriate dimension for the approximating manifold.
  • DimensionReduce[vecs] is equivalent to DimensionReduce[vecs,Automatic].
  • The vectors in the list data must be the same length as the .
  • DimensionReduce only works on numerical vectors all having the same length.
  • The following options can be given:
  • MethodAutomaticwhich reduction algorithm to use
    PerformanceGoalAutomaticaspect of performance to optimize
  • Possible settings for PerformanceGoal include:
  • "Quality"maximize reduction quality
    "Speed"maximize reduction speed
  • Possible settings for Method include:
  • Automaticautomatically chosen method
    "PrincipalComponentsAnalysis"principal components analysis method
    "LatentSemanticAnalysis"latent semantic analysis method
    "LowRankMatrixFactorization"use a low-rank matrix factorization algorithm

ExamplesExamplesopen allclose all

Basic Examples  (1)Basic Examples  (1)

Reduce the dimension of vectors:

Click for copyable input
Click for copyable input

Specify that the target dimension should be 1:

Click for copyable input
Introduced in 2015