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Originally Posted by yaser
There is not necessarily an expectation one way or the other. You should report whatever the data gives you.
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Professor Yaser: A trick question? Ouch!
Quote:
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Originally Posted by MLearning
In my case, when I plot the training data, I can verify that the data is linearly separable.
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The noise definition (.25*sin()) limits the size of the noise to fairly small values. And, this is fitting an arbitrary number of support vectors (in my test, up to 12 with .25 and up to 17 with 5.0) which greatly extends what is "linear". For comparison, question 12 could be answered on visual inspection of the plot.