R/LIB_SNN.R

In survivalSL: Super Learner for Survival Prediction from Censored Data

LIB_SNN <- function(times, failures, group=NULL, cov.quanti=NULL, cov.quali=NULL,
                      data, n.nodes, decay, batch.size, epochs){

  if(!(is.null(group))){
    .data <- data[,c(times, failures, group, cov.quanti, cov.quali)]
    } else{
    .data <- data[,c(times, failures, cov.quanti, cov.quali)]   }

  .f  <- as.formula(paste("Surv(", times, ",", failures, ")", "~."))

  .deepsurv <- survivalmodels::deepsurv(.f, data = .data,  verbose = FALSE, num_nodes=n.nodes,
                        weight_decay=decay, num_workers =0L,
                        batch_size=batch.size,
                        epochs=epochs)

  .time <- sort(unique(.data[,times]))

  .pred <- predict(.deepsurv, newdata = .data)
  .time.deepsurv<-as.numeric(dimnames(.pred)[[2]])

  idx=findInterval(.time, .time.deepsurv)
  .pred=.pred[,pmax(1,idx)]

  .obj <- list(model=.deepsurv,
          library="LIB_SNN",
          group=group, cov.quanti=cov.quanti, cov.quali=cov.quali,
          data=data.frame(times=data[,times], failures=data[,failures],
          data[, !(dimnames(data)[[2]] %in% c(times, failures))]), times=.time, predictions=.pred)

  class(.obj) <- "libsl"

  return(.obj)
}