Hello,
I can use mvpart function of library "mvpart" to get a decision tree. The
output of decision tree could be something like the following. I can use it
to manually calculate deviance explained by the variable in the first split
as below. There should be an easy way to tabulate deviance explained by all
variables. I cannot seem to find it. The function printcp gives you a nice
table with rel error which you can use to estimate R^2. But printcp gives
output for variously sized trees, not for variables entered into the model.
- Kumar Mainali
the deviance explained by cond =
*1 â (2857+491)/3905.98 = 0.1426 or 14.26%.*
* 1) root 295 3905.9860 4.806780 *
* 2) cond>=194.15 77 491.2468 2.493506 *
4) cond>=309.7 25 62.1600 1.440000 *
5) cond< 309.7 52 388.0000 3.000000 *
* 3) cond< 194.15 218 2857.1560 5.623853 *
*6) embed>=82.5 114 891.9649 4.017544 *
* ...........................................*
á§
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