Il 27/09/11 01:58, R. Michael Weylandt ha scritto:
Why exactly do you want to "stabilize" your results?
If it's in preparation for publication/classroom demo/etc., certainly
resetting the seed before each run (and hence getting the same sample()
output) will make your results exactly reproducibl
Why exactly do you want to "stabilize" your results?
If it's in preparation for publication/classroom demo/etc., certainly
resetting the seed before each run (and hence getting the same sample()
output) will make your results exactly reproducible. However, if you are
looking for a clearer picture
Hi, I'm working with support vector machine for the classification
purpose, and I have a problem about the accuracy of prediction.
I divided my data set in train (1/3 of enteire data set) and test (2/3
of data set) using the "sample" function. Each time I perform the svm
model I obtain differe
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