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https://stats.stackexchange.com/questions/146172/bounded-and-unbounded-support-vectors-for-nu-svms
How do we find out which of the support vectors for a nu-svm are its bounded or unbounded support vectors? For c-SVMs the test is easy: a support vector with $\alpha_i = C$ denotes a bounded support vector, while the others are unbounded.
https://www.stat.berkeley.edu/~arturof/Teaching/EE127/Notes/support_vector_machines.pdf
i is a support vector. Note that the support vectors that satisfy 0 i <C are the unbounded or free support vectors. 3.( i= C): Then by (22), y i wTx i+ b = 1 ˘ i, ˘ i 0, and x iis a SV. Note that the SVs with i= C are bounded support vectors; that is, they lie inside the margin. Furthermore, for 0 ˘ i <1, x i is correctly classi ed, but if ...
https://en.wikipedia.org/wiki/Support_vector_machine
Support-vector machine weights have also been used to interpret SVM models in the past. Posthoc interpretation of support-vector machine models in order to identify features used by the model to make predictions is a relatively new area of research with special significance in the biological sciences. History
https://stats.stackexchange.com/questions/146172/bounded-and-unbounded-support-vectors-for-nu-svms/189348
How do we find out which of the support vectors for a nu-svm are its bounded or unbounded support vectors? For c-SVMs the test is easy: a support vector with $\alpha_i = C$ denotes a bounded support vector, while the others are unbounded.
http://web.mit.edu/6.034/wwwbob/svm-notes-long-08.pdf
An Idiot’s guide to Support vector machines (SVMs) R. Berwick, Village Idiot SVMs: A New ... Support Vectors •Support vectors are the data points that lie closest to the decision surface (or hyperplane) ... •Support Vector Machine (SVM) finds an optimal solution. 4 Support Vector Machine (SVM) Support vectors Maximize
https://scikit-learn.org/stable/modules/svm.html
Support Vector Machines ... Support Vector Machine algorithms are not scale invariant, ... , 1]\) is an upper bound on the fraction of training errors and a lower bound of the fraction of support vectors. It can be shown that the \(\nu\)-SVC formulation is a reparameterization of the \(C\)-SVC and therefore mathematically equivalent.
https://stackoverflow.com/questions/36295365/more-training-set-errors-than-bounded-support-vectors
As long as there is a nonzero margin, training errors should be a subset of the bounded support vectors, since the bounded support vectors are training instances that are on the wrong side of the margin while training set errors are instance on the wrong side of the learned separator, which lies inside the margin.
https://pythonmachinelearning.pro/classification-with-support-vector-machines/
Classification with Support Vector Machines. ... These ‘s also tell us something very important about our SVM: they indicate the support vectors! If a particular point . is a support vector, ... The change is that our ‘s are also bounded above by . After solving for our ‘s, ...
https://www.csie.ntu.edu.tw/~cjlin/papers/bottou_lin.pdf
Support Vector Machine Solvers Figure 1: The optimal hyperplane separates positive and negative examples with the max-imal margin. The position of the optimal hyperplane is solely determined by the few examples that are closest to the hyperplane (the support vectors.) 2. Support Vector Machines
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