GenerateElbowPlotPCA: Create elbow plot to see how much total variance is explained...

Description Usage Arguments Value See Also

View source: R/preprocessing.R

Description

Create elbow plot to see how much total variance is explained by the components

Usage

1
GenerateElbowPlotPCA(inputted.data, column.to.do.PCA.on, scale.PCA)

Arguments

inputted.data

A dataframe.

column.to.do.PCA.on

A vector of strings that specify the column names that should be used for doing PCA.

scale.PCA

Boolean to specify whether or not to scale columns before doing PCA.

Value

No object is returned. A plot will be created.

See Also

Other Preprocessing functions: AddColBinnedToBinary(), AddColBinnedToQuartiles(), AddPCsToEnd(), ConvertDataToPercentiles(), CorAssoTestMultipleWithErrorHandling(), DownSampleDataframe(), GeneratePC1andPC2PlotsWithAndWithoutOutliers(), Log2TargetDensityPlotComparison(), LookAtPCFeatureLoadings(), 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.