({{, (RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction])[…] 
represents a function generated by (RefLink[DimensionReduction, paclet:ref/DimensionReduction]) that projects data onto a lower-dimensional approximating manifold.}})

OpenersNotesSection(Spacer1)Details and Options

(RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction]) works like (RefLink[Function, paclet:ref/Function]).

(RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction])[…][example] projects the single example example onto the approximating manifold.

(RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction])[…][{(Subscript[example, 1]),(Subscript[example, 2]),…}] projects all the (Subscript[example, i]).

(RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction])[…][data,prop] gives the specified property of the dimension reduction associated with data.

Possible properties include:

(RefLink[DimensionReduction, paclet:ref/DimensionReduction])[(RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction])[…],(RefLink[FeatureExtractor, paclet:ref/FeatureExtractor])->fe] can be used to prepend the (RefLink[FeatureExtractorFunction, paclet:ref/FeatureExtractorFunction])[…] fe to the existing feature extractor.

OpenersPrimaryExamplesSection(Spacer1)Examples  (4)

OpenersExampleSection0(Spacer1)Basic Examples  (3)

Generate a (RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction]) from a list of vectors:

dr=DimensionReduction[{{1,2,3},{2,3,5},{3,5,8},{4,5,8.5}}]

Use this reducer function on a new vector:

dr[{6,7,14}]

Use this reducer function on a list of new vectors:

dr[{{6,7,14},{5,6,11}, {1,3,4}}]

The vectors can also contain missing values:

dr[{{6,Missing[],14},{5,6,Missing[]}, {Missing[],3,4}}]

Generate a (RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction]) from a list of vectors:

dr=DimensionReduction[{{Missing[],2,3},{2,3,5},{3,Missing[],8},{4,5,8.5}}]

Use this reducer function on a list of new vectors:

newvectors={{6,7,14},{5,6,11}, {1,3,Missing[]}};

reduced=dr[newvectors]

Try to reconstruct the original vectors from the reduced ones:

dr[reduced,"OriginalVectors"]

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

dr[newvectors,"ReconstructedVectors"]

Generate a dimension reducer on a mixed-type dataset:

dr=DimensionReduction[{{1.4,"A"},{1.5,"A"},{2.3,"B"},{5.4,"B"}}]

Reduce the dimension of a new example:

dr[{2.4,"A"}]

OpenersExampleSection1(Spacer1)Scope  (1)

Generate a (RefLink[DimensionReducerFunction, paclet:ref/DimensionReducerFunction]) from a list of vectors:

dr=DimensionReduction[{{1,2,3},{2,3,5},{3,5,8},{4,5,8.5}}]

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

newvectors={{6,7,Missing[]},{5,Missing[],11}};

dr[newvectors, "ImputedVectors"]

({{DocumentationFooterIconsRelatedFunction.png, ({{See Also}, {(RefLink[DimensionReduction, paclet:ref/DimensionReduction])  ▪  (RefLink[DimensionReduce, paclet:ref/DimensionReduce])  ▪  (RefLink[ClassifierFunction, paclet:ref/ClassifierFunction])  ▪  (RefLink[PredictorFunction, paclet:ref/PredictorFunction])  ▪  (RefLink[LearnedDistribution, paclet:ref/LearnedDistribution])}})}})

({{DocumentationFooterIconsRelatedGuide.png, ({{Related Guides}, {▪(RefLinkPlain[Machine Learning, paclet:guide/MachineLearning])}})}})