Support vector machines are often considered to be black box learning algorithms. We show that for linear kernels it is possible to open this box and visually depict the content of the SVM classifier in high-dimensional space in the interactive format of a nomogram. We provide a crosscalibration method for obtaining probabilistic predictions from any SVM classifier, which control for the genera...
