Description Usage Arguments Details Author(s) References Examples
View source: R/rsfes.bs_predict.R
Prediction with new data and return a saved forest brier score function
1 | rsfes.bs_predict(rsfesfit, testdat, rii, trlength = 500)
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rsfesfit |
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testdat |
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rii |
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trlength |
Prediction with new data and return a saved forest brier score function
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 35 36 37 38 39 | ##---- 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, testdat, rii, trlength = 500)
{
trees = rsfesfit$pectrees
colindexes = rsfesfit$colindexes
newindexes = rsfesfit$newindexes
newdata = testdat[, -c(rii)]
if (trlength > length(rsfesfit$pectrees))
stop("Number of Trees for prediction should not be more than Number of Trees Fitted")
testpre <- NULL
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]])
}
newtestdat = cbind.data.frame(testdat[, c(rii)],
testdata)
pecerror <- pec(list(rsfse = trees[[i]]), formula = Surv(time,
status) ~ ., data = newtestdat, cens.model = "marginal",
reference = FALSE)
print((pecerror))
pecerror$AppErr$rsfse[is.na(pecerror$AppErr$rsfse)] = 0
predicts = crps(pecerror)[1]
print(crps(pecerror))
testpre <- cbind(predicts, testpre)
}
}
ensemble_predictions <- rowMeans(testpre)
return(ensemble_predictions)
}
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