View source: R/create.training.validation.split.R
create.training.validation.split | R Documentation |
Utility function to create random partitions of a dataset into training and validation sets. If samples are < 200, 66:34; otherwise 50:50 partitions are generated between training and validation sets respectively
create.training.validation.split(
exp.data = NULL, ann.data = NULL, seed.number = 51214
)
exp.data |
Feature by sample mRNA abundance matrix |
ann.data |
Sample by clinical attribute matrix |
seed.number |
Random seed for sampling |
A list of four matrices expression and two associated clinical matrices (exp.T, ann.T, exp.V and ann.V). One set for training and one for validation
Syed Haider
# load test data
x <- get.test.data(data.types = c("mRNA.T", "ann"));
# create training and validation sets
partitioned.datasets <- create.training.validation.split(
exp.data = x$mRNA.T$BLCA,
ann.data = x$ann$BLCA,
seed.number = 51214
);
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