Hello, In a particular application I was in need of machine learning (I know the things I studied in my undergraduate course). I used Support Vector Machines and got the problem solved. Its working fine. Now I need to improve the system. Problems here are I get additional training examples every week. Right now the system starts trai...
For LibSVM. In 'A Practical Guide to Support Vector Classification' it is suggested that to use m number to represent an m-category attribute. For example {red, green, blue} can be represented as (0,0,1), (0,1,0), (1,0,0). But in the README, it says value in the index:value pairs can only take a real number. Anyone knows how to repre...
With StompChicken's corrections (I miscomputed one dot product, ugh!) the answer appears to be yes. I have since tested the same problem using a precomputed kernel with the same correct results. If you are using libsvm StompChickens clear, organized computations are a very nice check. Original Question: I am about to start using precom...
I am using a multi-dimensional SVM classifier (SVM.NET, a wrapper for libSVM) to classify a set of features. Given an SVM model, is it possible to incorporate new training data without having to recalculate on all previous data? I guess another way of putting it would be: is an SVM mutable? ...
I'm cross-posting this from math.stackexchange.com because I'm not getting any feedback and it's a time-sensitive question for me. My question pertains to linear separability with hyperplanes in a support vector machine. According to Wikipedia: ...formally, a support vector machine constructs a hyperplane or set of hyperplane...