computeLaplacianEmbedding: Computes the Laplacian Eigenmap For Dimension Reduction
In nesscoder/TimeCycle: TimeCycle: Topology Inspired MEthod for the Detection of Cycling Transcripts
Description
Usage
Arguments
Value
See Also
View source: R/computeLaplacianEmbedding.R
Description
Takes a n-D Takens' Embedding and returns the 2-D Laplacian Eigenmap.
Usage
1
computeLaplacianEmbedding(takens)
Arguments
takens
a data.frame of the n-dimensional Takens' embedding. Columns defined from (1-D to n-D). TimeCycle defaults to n = 3.
Value
a data.frame of the 2-dimensional Takens' embedding. Columns defined by eigen vectors with last two non-trivial eigen values.
See Also
-
getPersistence for usage
-
matrixLaplacian for defining laplacian eigenmaps.
nesscoder/TimeCycle documentation built on June 29, 2021, 5:16 a.m.
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Description Usage Arguments Value See Also
View source: R/computeLaplacianEmbedding.R
Description
Takes a n-D Takens' Embedding and returns the 2-D Laplacian Eigenmap.
Usage
1 | computeLaplacianEmbedding(takens)
|
Arguments
takens |
a |
Value
a data.frame of the 2-dimensional Takens' embedding. Columns defined by eigen vectors with last two non-trivial eigen values.
See Also
-
getPersistencefor usage -
matrixLaplacianfor defining laplacian eigenmaps.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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