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#1
12-01-2018, 01:32 PM
 Colonel Smoothie Member CAS Join Date: Sep 2010 College: Jamba Juice University Favorite beer: AO Amber Ale Posts: 48,751
Support Vector Machines

Does anyone use SVM at work? I was reading a book and the author went over some examples where logistic regression would overfit, but SVM was more stable to outliers. That intrigues me. I have no experience with SVM at work, though.
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#2
12-07-2018, 12:37 AM
 Colonel Smoothie Member CAS Join Date: Sep 2010 College: Jamba Juice University Favorite beer: AO Amber Ale Posts: 48,751

ok the book says, linear SVM is almost equivalent to L2-regularized logistic regression
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#3
12-07-2018, 12:38 AM
 Colonel Smoothie Member CAS Join Date: Sep 2010 College: Jamba Juice University Favorite beer: AO Amber Ale Posts: 48,751

I guess the regularization is what reduces the overfitting
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#4
12-09-2018, 07:03 PM
 hostess Member CAS Join Date: Aug 2018 Posts: 584

SVM seems similar to KNN imo
#5
12-09-2018, 10:06 PM
 AbedNadir Member CAS SOA Join Date: Mar 2014 Studying for FCAS Posts: 2,367

haven't seen any real-life problems where it out-performs lightgbm. there may be some contrived examples where a kernel fits perfectly and makes separation but it would never happen on real data.
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#6
12-10-2018, 01:45 PM
 Colonel Smoothie Member CAS Join Date: Sep 2010 College: Jamba Juice University Favorite beer: AO Amber Ale Posts: 48,751

The book didn't really go into what the model form looks like. Are the parameters easy to explain? If not I suppose that is a good reason to stick with logistic regression.
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