LookAtPCFeatureLoadings: Principal component feature loadings
In yhhc2/machinelearnr: Package with various functions for preprocessing, clustering, and classification
Description
Usage
Arguments
Value
See Also
View source: R/preprocessing.R
Description
Principal component feature loadings
Usage
1
LookAtPCFeatureLoadings(pca.results, pc.to.look.at)
Arguments
pca.results
Object outputted from stats::prcomp()
pc.to.look.at
Numeric value indicating which principal component to look at.
Value
No objects are outputted but a plot is created.
See Also
Other Preprocessing functions:
AddColBinnedToBinary(),
AddColBinnedToQuartiles(),
AddPCsToEnd(),
ConvertDataToPercentiles(),
CorAssoTestMultipleWithErrorHandling(),
DownSampleDataframe(),
GenerateElbowPlotPCA(),
GeneratePC1andPC2PlotsWithAndWithoutOutliers(),
Log2TargetDensityPlotComparison(),
MultipleColumnsNormalCheckThenBoxCox(),
NormalCheckThenBoxCoxTransform(),
RanomlySelectOneRowForEach(),
RecodeIdentifier(),
RemoveColWithAllZeros(),
RemoveRowsBasedOnCol(),
RemoveSamplesWithInstability(),
SplitIntoTrainTest(),
StabilityTestingAcrossVisits(),
SubsetDataByContinuousCol(),
TwoSampleTTest(),
ZScoreChallengeOutliers(),
captureSessionInfo(),
correlation.association.test(),
describeNumericalColumnsWithLevels(),
describeNumericalColumns(),
generate.descriptive.plots.save.pdf(),
generate.descriptive.plots()
yhhc2/machinelearnr documentation built on Dec. 23, 2021, 7:19 p.m.
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Description Usage Arguments Value See Also
View source: R/preprocessing.R
Description
Principal component feature loadings
Usage
1 | LookAtPCFeatureLoadings(pca.results, pc.to.look.at)
|
Arguments
pca.results |
Object outputted from stats::prcomp() |
pc.to.look.at |
Numeric value indicating which principal component to look at. |
Value
No objects are outputted but a plot is created.
See Also
Other Preprocessing functions:
AddColBinnedToBinary(),
AddColBinnedToQuartiles(),
AddPCsToEnd(),
ConvertDataToPercentiles(),
CorAssoTestMultipleWithErrorHandling(),
DownSampleDataframe(),
GenerateElbowPlotPCA(),
GeneratePC1andPC2PlotsWithAndWithoutOutliers(),
Log2TargetDensityPlotComparison(),
MultipleColumnsNormalCheckThenBoxCox(),
NormalCheckThenBoxCoxTransform(),
RanomlySelectOneRowForEach(),
RecodeIdentifier(),
RemoveColWithAllZeros(),
RemoveRowsBasedOnCol(),
RemoveSamplesWithInstability(),
SplitIntoTrainTest(),
StabilityTestingAcrossVisits(),
SubsetDataByContinuousCol(),
TwoSampleTTest(),
ZScoreChallengeOutliers(),
captureSessionInfo(),
correlation.association.test(),
describeNumericalColumnsWithLevels(),
describeNumericalColumns(),
generate.descriptive.plots.save.pdf(),
generate.descriptive.plots()
R Package Documentation
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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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