Implementing a linear, binary SVM (support vector machine)

Question

I want to implement a simple SVM classifier, in the case of high-dimensional binary data (text), for which I think a simple linear SVM is best. The reason for implementing it my

Answer 1

The following paper "Pegasos: Primal Estimated sub-GrAdient SOlver for SVM" top of page 11 describes the Pegasos algorithm also for kernels.It can be downloaded from http://ttic.uchicago.edu/~nati/Publications/PegasosMPB.pdf

It appears to be a hybrid of coordinate descent and subgradient descent. Also, line 6 of the algorithm is wrong. In the predicate the second appearance of y_i_t should be replaced with y_j instead.