Fig. 4: Non-linear Support Vector Machine (SVM) using distributed feedback.

The SONAR dataset consisted of 97 measurements of rocks (a) and 111 measurements of cylinders (b). c Applying a linear SVM directly to the training data resulted in a classification accuracy of 75%. d After using the optical platform to perform a non-linear random projection on the SONAR data, the SVM accuracy increased to 90.4%.