filter.pca: filter.pca
In enriquea/feseR: Feature Selection workflow in R
Description
Usage
Arguments
Value
Description
Compute Principal Components from input matrix. Control how many components must be returned.
Usage
1
filter.pca(features, center = TRUE, scale = TRUE, cum.var.cutoff = 1)
Arguments
features
A numeric matrix as input.
center
Must the features be centered (default TRUE).
scale
Must the features be scaled (default TRUE).
cum.var.cutoff
Cumulative variance proportion cutoff. Used to return the Principal Componets (PCs) which satisfies that value. If 1 (default), all PCs will be returned.
Value
A matrix of Principal components.
enriquea/feseR documentation built on March 30, 2021, 4:12 p.m.
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Description Usage Arguments Value
Description
Compute Principal Components from input matrix. Control how many components must be returned.
Usage
1 | filter.pca(features, center = TRUE, scale = TRUE, cum.var.cutoff = 1)
|
Arguments
features |
A numeric matrix as input. |
center |
Must the features be centered (default TRUE). |
scale |
Must the features be scaled (default TRUE). |
cum.var.cutoff |
Cumulative variance proportion cutoff. Used to return the Principal Componets (PCs) which satisfies that value. If 1 (default), all PCs will be returned. |
Value
A matrix of Principal components.
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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