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2001
2010 Nov 18
1
predict() an rpart() model: how to ignore missing levels in a factor
...infrequently or singly. when the data set is randomly
split, it may be that the first data set has a crop type which is not
present in the second and so using predict() I get the error:
Error in model.frame.default(Terms, newdata, na.action = na.action, xlev =
attr(object, :
factor 'factor(c2001)' has new level(s) 13, 24, 35
where c2001 is the crop. I would like the predict function to ignore these
records. is there a command which will allow this as part of the predict()
function? With those with a small number of records (eg. 3-4), I would hope
some of the models would have the righ...