DownSampleDataframe: Down sample an imbalanced dataset to get a balanced dataset

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

Description

Down sample an imbalanced dataset to get a balanced dataset

Usage

DownSampleDataframe(input.data, name.of.feature.to.balance.on, seedVal)

Arguments

input.data	A dataframe.
name.of.feature.to.balance.on	Name of column in the input dataframe. Column has to be a factor. This column is the membership column that you want to balance for.
seedVal	Numeric value to set seed for random number generator.

Value

List with two objects:

1. ordered_balanced_data Dataframe with order of columns the same as the original data. Dataframe is a subset of the original dataframe because some observations were left out in order to balance the values in the selected column.

2. left_out_data Dataframe of the left out observations.

See Also

Other Preprocessing functions: AddColBinnedToBinary(), AddColBinnedToQuartiles(), AddPCsToEnd(), ConvertDataToPercentiles(), CorAssoTestMultipleWithErrorHandling(), GenerateElbowPlotPCA(), 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.