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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