prediction_discard.RdAd-hoc technique that discards censored observations from the analysis
prediction_discard(train.data, test.data, xnam, tao, ens.library, tuneparams = NULL)
| 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. |
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| 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. |
a list with the predictions of each machine learning algorithm and the AUC of each of them