DimensionReduce

DimensionReduce[{example1,example2,}]

projects the examples examplei to a lower-dimensional approximating manifold.

DimensionReduce[examples,n]

projects onto an approximating manifold in n-dimensional space.

Details and Options

  • DimensionReduce can be used on many types of data, including numerical, textual, sounds, and images, as well as combinations of these.
  • Each examplei can be a single data element, a list of data elements, an association of data elements, or a Dataset object.
  • DimensionReduce[examples] automatically chooses an appropriate dimension for the approximating manifold.
  • DimensionReduce[examples] is equivalent to DimensionReduce[examples,Automatic].
  • The following options can be given:
  • FeatureExtractorIdentityhow to extract features from which to learn
    FeatureNamesAutomaticnames to assign to elements of the examplei
    FeatureTypesAutomaticfeature types to assume for elements of the examplei
    MethodAutomaticwhich reduction algorithm to use
    PerformanceGoalAutomaticaspect of performance to optimize
    RandomSeeding1234what seeding of pseudorandom generators should be done internally
  • Possible settings for PerformanceGoal include:
  • "Quality"maximize reduction quality
    "Speed"maximize reduction speed
  • Possible settings for Method include:
  • Automaticautomatically chosen method
    "LatentSemanticAnalysis"latent semantic analysis method
    "Linear"automatically choose the best linear method
    "LowRankMatrixFactorization"use a low-rank matrix factorization algorithm
    "PrincipalComponentsAnalysis"principal components analysis method
    "TSNE"t-distributed stochastic neighbor embedding algorithm
    "AutoEncoder"use a trainable autoencoder
  • For Method -> "TSNE", The following suboptions are supported:
  • "Perplexity"Automaticperplexity value to be used
    "LinearPrereduction"Falsewhether to perform a light linear pre-reduction before running the t-SNE algorithm
  • Possible settings for RandomSeeding include:
  • Automaticautomatically reseed every time the function is called
    Inheriteduse externally seeded random numbers
    seeduse an explicit integer or strings as a seed

Examples

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Basic Examples  (2)

Reduce the dimension of vectors:

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Specify that the target dimension should be 1:

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Reduce the dimension of a mixed-type dataset:

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Scope  (6)

Options  (5)

Applications  (1)

See Also

DimensionReduction  DimensionReducerFunction  FeatureExtract  PrincipalComponents  ClusterClassify  Classify  Predict  ListSurfacePlot3D

Introduced in 2015
(10.1)
| Updated in 2017
(11.2)