TwoSampleTTest: Performs two sample t-test on multiple features

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

Description

Performs two sample t-test on multiple features

Usage

TwoSampleTTest(
  input.data,
  column.names.to.use,
  name.of.class.column,
  file.name
)

Arguments

input.data	A dataframe.
column.names.to.use	Vector of strings where each string is the name of a column of numerical data to use for t-test.
name.of.class.column	Name of column that contains labels for group1 and labels for group2. The labels can be any value. For example, for group1 observations can have value of "1" for this column while group2 observations can have value of "2" for this column.
file.name	Name of the file to write output to.

Value

Dataframe where the rows are statistic values from the t-test and columns are the features.

See Also

Other Preprocessing functions: AddColBinnedToBinary(), AddColBinnedToQuartiles(), AddPCsToEnd(), ConvertDataToPercentiles(), CorAssoTestMultipleWithErrorHandling(), DownSampleDataframe(), GenerateElbowPlotPCA(), GeneratePC1andPC2PlotsWithAndWithoutOutliers(), Log2TargetDensityPlotComparison(), LookAtPCFeatureLoadings(), MultipleColumnsNormalCheckThenBoxCox(), NormalCheckThenBoxCoxTransform(), RanomlySelectOneRowForEach(), RecodeIdentifier(), RemoveColWithAllZeros(), RemoveRowsBasedOnCol(), RemoveSamplesWithInstability(), SplitIntoTrainTest(), StabilityTestingAcrossVisits(), SubsetDataByContinuousCol(), 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.