# SVM Weighting

Hello,

I would be grateful to anyone who could explain me the working of SVM Weighting, I have used RapidMiner in extensively in my thesis, and I have to explain these operators in my document. I read the description of SVM Weighting in the RapidMIner manual but I could not understand it well.

Thanks!

Regards

I would be grateful to anyone who could explain me the working of SVM Weighting, I have used RapidMiner in extensively in my thesis, and I have to explain these operators in my document. I read the description of SVM Weighting in the RapidMIner manual but I could not understand it well.

Thanks!

Regards

0

## Answers

13Contributor IIa linear SVM (support vector machine), in very short, builds a linear model R^d -> {+1, -1} given by the equation

Y = sign(w*X+b)

Y = sign( sum

^{d}_{i=1}(w_{i}*X_{i}) +b).The absolute value of the ith entrance in the weight-vector w resembles the influence of the ith feature, given the all features are normalized.

The SVMWeighting operator now calculates such a linear model and returns the absolutes values of the weight vector.

You should note, that two features which are highly correlated share the importance score, giving them a lower score even if they are "important" for the class variable. For this case, you should better try Recursive Feature Elimination (RFE)

For a better description of SVM see http://research.microsoft.com/en-us/um/people/cburges/papers/svmtutorial.pdf

and for Recursive Feature Elimination using the weight vector of an SVM see

@article{Guyon/etal/2002,

author = "Isabelle Guyon and Jason Weston and Stephen Barnhill and Vladimir Vapnik",

title = "Gene Selection for Cancer Classification using Support Vector Machines",

journal = "Machine Learning",

volume = "46",

number = "1-3",

publisher = "Kluwer Academic Publishers, Boston",

pages = "389--422",

year = "2002",

}

Greetings

Ben

72MavenA very readable book on SVM is by Dr. Lutz Hamel, published by Wiley.

HTH

22Maven