extractFDAFPCA: Extract functional principal component analysis features.
In riebetob/mlr: Machine Learning in R
Description
Usage
Arguments
Value
See Also
View source: R/extractFDAFeaturesMethods.R
Description
The function extracts the functional principal components from a data.frame
containing functional features.
Usage
1
extractFDAFPCA(pve = 0.99, npc = NULL)
Arguments
pve
[numeric]
Fraction of variance explained for the functional principal components.
Default is 0.99.
npc
[integer]
Number of principal components to extract. Overrides pve param.
Default is NULL
Value
[data.frame].
See Also
Other fda_featextractor: extractFDAFourier,
extractFDAMultiResFeatures,
extractFDAWavelets
riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.
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Description Usage Arguments Value See Also
View source: R/extractFDAFeaturesMethods.R
Description
The function extracts the functional principal components from a data.frame containing functional features.
Usage
1 | extractFDAFPCA(pve = 0.99, npc = NULL)
|
Arguments
pve |
[ |
npc |
[ |
Value
[data.frame].
See Also
Other fda_featextractor: extractFDAFourier,
extractFDAMultiResFeatures,
extractFDAWavelets
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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