Description Usage Arguments Value See Also Examples
Return data.sets as a list of training set, holdout set and validation set according to the predefined percentage of each partition default is a 50-50 split into training and holdout, no testing set code class/label/phenotypes as 1 and -1. User can manage the simulation data to be dichotomious/quantitative using label (class/qtrait)
1 2 3 4 5 6 7 | splitDataset(
all.data = NULL,
pct.train = 0.5,
pct.holdout = 0.5,
pct.validation = 0,
label = "class"
)
|
all.data |
A data frame of n rows by d colums of data plus a label column |
pct.train |
A numeric percentage of samples to use for traning |
pct.holdout |
A numeric percentage of samples to use for holdout |
pct.validation |
A numeric percentage of samples to use for testing |
label |
A character vector of the data column name for the outcome label. class for classification and qtrait for regression. |
A list containing:
traing data set
holdout data set
validation data set
Other simulation:
createInteractions()
,
createMainEffects()
,
createMixedSimulation()
,
createSimulation()
1 2 | data("rsfMRIcorrMDD")
data.sets <- splitDataset(rsfMRIcorrMDD)
|
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