RemoveSamplesWithInstability: Remove samples that have multiple values for a single column...

In yhhc2/machinelearnr: Package with various functions for preprocessing, clustering, and classification

Description

This function uses the StabilityTestingAcrossVisits() function, and then uses the results to subset the inputted data.

Usage

RemoveSamplesWithInstability(
  inputted.data,
  col.name.of.unique.identifier,
  value.to.evaluate,
  standard.deviation.threshold
)

Arguments

inputted.data	A dataframe
col.name.of.unique.identifier	A string that specifies name of column in inputted.data containing unique identifiers.
value.to.evaluate	A string that specifies name of column in inputted.data to look at for stability of values.
standard.deviation.threshold	A numeric value that specifies the value of the standard deviation that is considered large enough to say vists for a single sample is too unstable.

Details

Samples with only a single visit are removed. Additionally, samples that have values that differ significantly (stddev greater than a specified threshold) are also removed.

Value

A dataframe where only rows from stable samples remain.

See Also

Other Preprocessing functions: AddColBinnedToBinary(), AddColBinnedToQuartiles(), AddPCsToEnd(), ConvertDataToPercentiles(), CorAssoTestMultipleWithErrorHandling(), DownSampleDataframe(), GenerateElbowPlotPCA(), GeneratePC1andPC2PlotsWithAndWithoutOutliers(), Log2TargetDensityPlotComparison(), LookAtPCFeatureLoadings(), MultipleColumnsNormalCheckThenBoxCox(), NormalCheckThenBoxCoxTransform(), RanomlySelectOneRowForEach(), RecodeIdentifier(), RemoveColWithAllZeros(), RemoveRowsBasedOnCol(), SplitIntoTrainTest(), StabilityTestingAcrossVisits(), SubsetDataByContinuousCol(), TwoSampleTTest(), ZScoreChallengeOutliers(), captureSessionInfo(), correlation.association.test(), describeNumericalColumnsWithLevels(), describeNumericalColumns(), generate.descriptive.plots.save.pdf(), generate.descriptive.plots()

Examples

identifier.col <- c("a", "a", "a", "b", "b", "b", "c")
value.col <- c(1, 2, 3, 1, 1, 1, 5)
input.data.frame <- as.data.frame(cbind(identifier.col, value.col))

results <- RemoveSamplesWithInstability(input.data.frame, "identifier.col", "value.col", 0.5)

results

yhhc2/machinelearnr documentation built on Dec. 23, 2021, 7:19 p.m.