Hi Andreas,
Andreas Wittmann wrote:
Dear R-Users,
i want to use the function svm of the e1071 package to predict missing data
############################################################
data(iris)
## create missing completely at random data
for (i in 1:5)
{
mcar <- rbinom(dim(iris)[1], size=1, prob=0.1)
iris[mcar == 1, i] <- NA
}
ok <- complete.cases(iris)
model <- svm(Species ~ ., data=iris[ok,])
## try to predict the missing values for Species
## neither
pred <- predict(model, iris[5])
## nor
pred <- predict(model, iris[!ok, -5])
## seems to work....
ind <- is.na(iris[,5]) & !apply(iris[,-5], 1, function(x) any(is.na(x))
predict(model, iris[ind,-5])
Best,
Jim
Many thanks if anyone could tell me what i do wrong and what is the
problem here.
best regards
Andreas
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and provide commented, minimal, self-contained, reproducible code.
