create.classifier.univariate {SIMMS} | R Documentation |
Trains and tests a univariate (per subnetwork module) survival model
Description
Trains a model on training datasets. Predicts the risk score for all the
training & datasets, independently. This function also predicts the risk
score for combined training datasets cohort and validation datasets cohort.
The risk score estimation is done by multivariate models fit by
fit.survivalmodel
. The function also predicts risk scores for each of
the top.n.features
independently.
Usage
create.classifier.univariate(
data.directory = ".",
output.directory = ".",
feature.selection.datasets = NULL,
feature.selection.p.threshold = 0.05,
training.datasets = NULL,
validation.datasets = NULL,
top.n.features = 25,
models = c("1", "2", "3")
)
Arguments
data.directory |
Path to the directory containing datasets as specified
by |
output.directory |
Path to the output folder where intermediate and results files will be saved |
feature.selection.datasets |
A vector containing names of datasets used
for feature selection in function |
feature.selection.p.threshold |
One of the P values that were used for
feature selection in function |
training.datasets |
A vector containing names of training datasets |
validation.datasets |
A vector containing names of validation datasets |
top.n.features |
A numeric value specifying how many top ranked features will be used for univariate survival modelling |
models |
A character vector specifying which of the models ('1' = N+E, '2' = N, '3' = E) to run |
Value
The output files are stored under output.directory
/output/
Author(s)
Syed Haider
Examples
# see package's main documentation