fit.survivalmodel: Trains a multivariate survival model

In SIMMS: Subnetwork Integration for Multi-Modal Signatures

Trains a multivariate survival model

Description

Trains a multivariate survival model and conducts feature selection using both backward elimination and forward selection, independently. TO BE DEPRECATED AND HAS BEEN REPLACED BY create.classifier.multivariate

Usage

fit.survivalmodel(
  data.directory = ".",
  output.directory = ".",
  feature.selection.datasets = NULL,
  feature.selection.p.threshold = 0.05,
  training.datasets = NULL,
  top.n.features = 25,
  models = c("1", "2", "3")
)

Arguments

data.directory	Path to the directory containing datasets as specified by feature.selection.datasets, training.datasets
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 derive.network.features()
feature.selection.p.threshold	One of the P values that were used for feature selection in function derive.network.features(). This function does not support vector of P values as used in derive.network.features() for performance reasons
training.datasets	A vector containing names of training datasets to be used to train multivariate survival model
top.n.features	A numeric value specifying how many top ranked features will be used to train the multivariate survival model
models	A character vector specifying which models ('1' = N+E, '2' = N, '3' = E) to run

Value

The output files are stored under output.directory/output/

Author(s)

Syed Haider

See Also

create.classifier.multivariate

Examples

# see package's main documentation

SIMMS documentation built on April 24, 2022, 5:06 p.m.