Hello,
Frank was nice enough to point me to the val.prob function of the Design
library.
It creates a beautiful graph that really helps me visualize how well my
model is predicting probabilities.
By default, there are two lines on the graph
1) fitted logistic calibration curve
2) nonparametric fit using lowess
Right now, the nonparametric line doesn't look very good.
The "fitted logistic" line looks great. It is right next to the "ideal"
line!!
If I am understanding the graph correctly, whatever transformation the
val.prob is doing to my predicted probability is making it really accurate.
Is there some standard function in R that will let me do the same
transformation? (I guess the long way around would be to tear into the
actual val.prob function and try to reverse engineer what he's doing.
But there must be something easier.)
Anybody have any suggestions?
Thanks!
-N
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