Hi,
I'm switch over from RapidMiner to R. (The learning curve is steep, but
there is so much more I can do with R and it runs much faster overall.)
In RapidMiner, I can "tune" a parameter of my svm in a nice cross
validation loop. The process will print out the progress as it goes.
So for a 5x cross tuning for the value of C with auc as my performance
measure, I see
XV C AUC
1 1 .5
2 1 .48
3 1 .51
4 1 .52
1 2 .52
2 2 .54
3 2 .53
4 2 .52
1 3 .6
2 3 .61
3 3 .6
4 3 .59
etc...
RapidMiner then takes the average for each value of C and reports back
the best one.
RapidMiner will even graph the progress with C on the X axis and AUC on
the Y axis so I can see how the process is doing. (This is nice when
training a large range of C so I can tell if it is worth stopping the
process early.
I can even train 2 or more variables at a time in a big "grid" of
combination is 5x cross validation for each combo. i.e. 10 values for C
and 10 values for gamma gives 100 combinations with 5x cross validation
for each for a total of 500 executions.
Is there anyway to do something similar to this in R. I've come across
the "tune" function, but don't entirely understand all the options.
Additionally, I don't see how to output the progress as it goes. (also,
setting number of XV, averaging of scores, etc.)
Does anybody have any ideas?
Thanks
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