<p>I'm comparing the results of an Newton optimizer for a modified version of SVM ( a generalized quadratic loss, similar to the one stated in:</p>

<p><a href="http://www.frontiersinai.com/ecai/ecai2004/ecai04/pdf/p0628.pdf" rel="nofollow noreferrer">A generalized quadratic loss for SVM</a></p>

<p>) with classic SVM^light for regression. The problem is that it's able to overfit the data (UCI Yacht data-set) but I can't reach the generalization results of SVM^light. I've tried several hyper-parameters grids. I'm solving the primal problem. I'll send you my code if you need it. Any suggestion?</p>

CC BY-SA 4.0
2019-11-26T12:56:05.620Z
I figured out I've not shuffled the whole data-set (training+validation+test).
Now it generalizes in a better way (at least on the UCI Yacht data-set)
filippo portera
CC BY-SA 4.0
2019-12-17T10:33:24.023Z
I was wrong. I tried a different shuffle and the problem still persist.
Filippo Portera
<objective-functions><support-vector-machine>
A generalized quadratic loss and Newton iteration for Support Vector Regression, why doesn't it generalize well?
filippo portera
# A generalized quadratic loss and Newton iteration for Support Vector Regression, why doesn't it generalize well?

(Asked by: username_0 on 2019-11-26)

I'm comparing the results of an Newton optimizer for a modified version of SVM ( a generalized quadratic loss, similar to the one stated in:

[A generalized quadratic loss for SVM](http://www.frontiersinai.com/ecai/ecai2004/ecai04/pdf/p0628.pdf)

) with classic SVM^light for regression. The problem is that it's able to overfit the data (UCI Yacht data-set) but I can't reach the generalization results of SVM^light. I've tried several hyper-parameters grids. I'm solving the primal problem. I'll send you my code if you need it. Any suggestion?

**Tags:** objective-functions, support-vector-machine

> **Comments:**
> **username_0**: I figured out I've not shuffled the whole data-set (training+validation+test). Now it generalizes in a better way (at least on the UCI Yacht data-set)  
> **username_1**: I was wrong. I tried a different shuffle and the problem still persist.  

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## 0 answers

