Hi,
I am using one class svm for binary classification and was just curious
what is the range/scale for sample weights? Are they normalized internally?
For example -
Sample 1, weight - 1
Sample 2, weight - 10
Sample 3, weight - 100
Does this mean Sample 3 will always be predicted as positive and
Hi Abhishek,
think of your example as being equivalent to putting 1 of sample 1, 10 of
sample 2 and 100 of sample 3 in a dataset and then run your SVM.
This is exactly true for some estimators and approximately true for others,
but always a good intuition.
Hope this helps!
Michael
On Fri, Jul 2
Hi Michael, thanks for the response. Based on what you said, is it correct
to assume that weights are relative to the size of the data set? Eg
If my dataset size is 200 and I have 1 of sample 1, 10 of sample 2 and 100
of sample 3, sample 3 will be given a lot of focus during training because
it ex
Well, that will depend on how your estimator works. But in general you are
right - if you assume that samples 4 to N are weighted with the same weight
(e.g. 1) in both cases, then the sample 3 will be relatively less important
in the larger training set.
On Fri, Jul 28, 2017 at 1:06 PM, Abhishek R
