computePCADim: Number of features to use
In dibbelab/gficf: Gene Frequency - Inverse Cell Frequency
View source: R/dimensinalityReduction.R
computePCADim R Documentation
Number of features to use
Description
Compute the number of dimension to use for either PCA or LSA.
Usage
computePCADim(data, randomized = T, subsampling = F, plot = T)
Arguments
data
list; GFICF object
randomized
logical; Use randomized (faster) version for matrix decomposition (default is TRUE).
subsampling
logical; Use only a subset of the data for the imputation of dimensions to use.
plot
logical; Show eblow plot.
dibbelab/gficf documentation built on Nov. 2, 2022, 2:28 a.m.
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View source: R/dimensinalityReduction.R
| computePCADim | R Documentation |
Number of features to use
Description
Compute the number of dimension to use for either PCA or LSA.
Usage
computePCADim(data, randomized = T, subsampling = F, plot = T)
Arguments
data |
list; GFICF object |
randomized |
logical; Use randomized (faster) version for matrix decomposition (default is TRUE). |
subsampling |
logical; Use only a subset of the data for the imputation of dimensions to use. |
plot |
logical; Show eblow plot. |
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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