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.
- 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:
Method Automatic which reduction algorithm to use PerformanceGoal Automatic aspect of performance to optimize
- Possible settings for PerformanceGoal include:
"Quality" maximize reduction quality "Speed" maximize reduction speed
- Possible settings for Method include:
Automatic automatically chosen method "PrincipalComponentsAnalysis" principal components analysis method "LatentSemanticAnalysis" latent semantic analysis method "LowRankMatrixFactorization" use a low-rank matrix factorization algorithm
Introduced in 2015