Displaying 2 results from an estimated 2 matches for "predicted1".
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2011 Jun 02
1
aucRoc in caret package [SEC=UNCLASSIFIED]
Hi all,
I used the following code and data to get auc values for two sets of predictions:
library(caret)
> table(predicted1, trainy)
trainy
hard soft
1 27 0
2 11 99
> aucRoc(roc(predicted1, trainy))
[1] 0.5
> table(predicted2, trainy)
trainy
hard soft
1 27 2
2 11 97
> aucRoc(roc(predicted2, trainy))
[1] 0.8451621
predicted1:
1 1 2 2 2 1 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2...
2008 Apr 15
1
Predicting ordinal outcomes using lrm{Design}
...-0.23
---------------------------------------
I get excellent fits using
fit1 <-lrm(y ~ x1+x2, data=my.dataframe1)
Now I want to see how well my model can predict y for a new set of 4000
observations. I need to predict y for each new observation *individually*.
I know an expression like
predicted1<-predict(fit1, newdata=my.dataframe2, type=""fitted.ind")
can give *probability* of each of the 4 possible responses for each
observation. So my questions are
(1) How do I pick the likeliest y (i.e., likeliest of the 4 possible
ratings) for each given new observation?
(2)...