prediction_discard: Prediction discarding censored observations

In pablogonzalezginestet/ensBagg: Stacked IPCW Bagging

Prediction discarding censored observations

Description

Ad-hoc technique that discards censored observations from the analysis

Usage

prediction_discard(train.data, test.data, xnam, tao, ens.library,
  tuneparams = NULL)

Arguments

train.data	a data.frame with at least the following variables: event-times (censored) in the first column, event indicator in the second column and covariates/features that the user potentially want to use in building the preodiction model. Censored observations must be denoted by the value 0. Main event of interest is denoted by 1.
test.data	a data.frame with the same variables and names that the train.data
xnam	vector with the names of the covariates to be included in the model
tao	evaluation time point of interest
tuneparams	a list of tune parameters for each machine learning procedure. Name them as gam_param, lasso_param, randomforest_param, svm_param, bart_param, knn_param, nn_param. Default values are the same used for the simulation.

Value

a list with the predictions of each machine learning algorithm and the AUC of each of them

pablogonzalezginestet/ensBagg documentation built on Aug. 25, 2023, 3:23 a.m.