DimensionReducerFunction

represents a function generated by DimensionReduction that projects data onto a lower-dimensional approximating manifold.

Details and Options

DimensionReducerFunction works like Function.
DimensionReducerFunction[…][example] projects the single example example onto the approximating manifold.
DimensionReducerFunction[…][{example₁,example₂,…}] projects all the example_i.
DimensionReducerFunction[…][data,prop] gives the specified property of the dimension reduction associated with data.
Possible properties include:

	"ReducedVectors"	reduction of the vectors given
	"OriginalData"	deduced original examples given reduced vectors
	"ReconstructedData"	reconstruction by reduction and inversion
	"ImputedData"	missing values replaced by imputed ones

DimensionReduction[DimensionReducerFunction[…],FeatureExtractorfe] can be used to prepend the FeatureExtractorFunction[…] fe to the existing feature extractor.

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Generate a DimensionReducerFunction from a list of vectors:

Use this reducer function on a new vector:

Use this reducer function on a list of new vectors:

The vectors can also contain missing values:

Generate a DimensionReducerFunction from a list of vectors:

Use this reducer function on a list of new vectors:

Try to reconstruct the original vectors from the reduced ones:

The reconstructed vectors can be directly obtained from the original vectors:

Generate a dimension reducer on a mixed-type dataset:

Reduce the dimension of a new example:

Generate a DimensionReducerFunction from a list of vectors:

Use the reducer function to impute missing values in other vectors:

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