Description Usage Arguments Details Author(s) References Examples
View source: R/rsfes.surv_predict.R
Prediction with new data and return a saved forest with mean surv prob at each time points
| 1 | rsfes.surv_predict(rsfesfit, newdata, uniquetimes, trlength = 500)
 | 
| rsfesfit | |
| newdata | |
| uniquetimes | |
| trlength | 
Prediction with new data and return a saved forest with mean surv prob at each time points
Hong Wang
Random Survival Forest with Space Extensions for Censored Data, submitted to Artificial Intelligence in Medicine
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.
## The function is currently defined as
function (rsfesfit, newdata, uniquetimes, trlength = 500) 
{
    trees = rsfesfit$pectrees
    colindexes = rsfesfit$colindexes
    newindexes = rsfesfit$newindexes
    if (trlength > length(rsfesfit$pectrees)) 
        stop("Number of Trees for prediction should not be more than Number of Trees Fitted")
    testpre <- matrix(0, nrow = dim(newdata)[1], ncol = length(uniquetimes))
    colnames(testpre) = paste0(uniquetimes)
    for (i in 1:trlength) {
        {
            if (ncol(newdata) <= 100) {
                testdata = extspace_testdat(newdata, newindexes[[i]])
                testdata = testdata[, colindexes[[i]]]
            }
            else {
                testdata = newdata[, colindexes[[i]]]
                testdata = extspace_testdat(testdata, newindexes[[i]])
            }
            testdata = as.data.frame(testdata)
            predicts = predictSurvProb(trees[[i]], testdata, 
                uniquetimes)
            predicts[is.na(predicts)] = 0
            colnames(predicts) = paste0(uniquetimes)
            testpre <- testpre + predicts
        }
    }
    return(testpre/trlength)
  }
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