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I am running ksvm in R(using kernlab package) for a highly imbalanced data.Is there any way i can get the distance of my test data points(each of dimension 8-10) from the hyperplane?so that i can conclude the far one point is from the hyperplane the more it belongs to that class(except misclassified points).is there any other package in R which can give me that distance?(even if not given directly how can i compute?)

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closed as off-topic by Sycorax, Xi'an, gung, Andy, John Mar 16 '16 at 23:45

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The distances will be returned by calling the predict function on the model, the test data, and type = "decision" . See http://www.inside-r.org/packages/cran/kernlab/docs/predict.ksvm

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