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Old 04-15-2012, 10:37 PM
sakumar sakumar is offline
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Default HW 2.8: Seeking clarification on simulated noise

First we generate a training set of 1000 points. We also generate a vector y using the target function given.

Now we are directed to randomly flip the sign of 10% of the training set.

The training set has 4000 numbers at this point. We should randomly choose 400 of these numbers and flip the sign? Including the y values? Also include the values for the 1000 x0 which we initialized to 1.0?
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Old 04-15-2012, 11:42 PM
jsarrett jsarrett is offline
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Default Re: HW 2.8: Seeking clarification on simulated noise

I'm pretty sure we only flip the sign on the ys. That's what I did and got reasonable results. That corresponds to noise in your sample of the target function.

-James
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Old 04-16-2012, 12:03 AM
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yaser yaser is offline
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Default Re: HW 2.8: Seeking clarification on simulated noise

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Originally Posted by jsarrett View Post
I'm pretty sure we only flip the sign on the ys. That's what I did and got reasonable results. That corresponds to noise in your sample of the target function.

-James
You are correct.
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Old 04-16-2012, 07:18 AM
sakumar sakumar is offline
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Default Re: HW 2.8: Seeking clarification on simulated noise

Thank you both for that clarification. I believe I am inching closer to understanding noise.

I have some follow up questions: How is E_in defined? Do you compare the linear regression results (i.e. sign(w'x) where w is obtained by linear regression using the "noisy" y) to the true value of y or to the the noisy value from the training data?

In the real world, since the target function is unknown, the best one can do is E_in_estimated by comparing sign(w'x) to the "noisy" y. But in this instance we actually do have the target function. So if we are asked to compute E_in should we use the original y?

Edit: I tried both and the closest answer didn't change, but I'd still like to understand the correct definition of E_in.
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Old 04-16-2012, 01:55 PM
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htlin htlin is offline
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Default Re: HW 2.8: Seeking clarification on simulated noise

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Originally Posted by sakumar View Post
Thank you both for that clarification. I believe I am inching closer to understanding noise.

I have some follow up questions: How is E_in defined? Do you compare the linear regression results (i.e. sign(w'x) where w is obtained by linear regression using the "noisy" y) to the true value of y or to the the noisy value from the training data?

In the real world, since the target function is unknown, the best one can do is E_in_estimated by comparing sign(w'x) to the "noisy" y. But in this instance we actually do have the target function. So if we are asked to compute E_in should we use the original y?

Edit: I tried both and the closest answer didn't change, but I'd still like to understand the correct definition of E_in.
You should compare to the noisy y that you have on hand. Hope this helps.
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Old 04-16-2012, 06:07 PM
markweitzman markweitzman is offline
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Default Re: HW 2.8: Seeking clarification on simulated noise

What about with Eout? Do we also compare with noisy y or with y without noise?
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