On Fri, 1 Sep 2017, Artur T. wrote: > Dear all, > > I am just experimenting with libsvm. [...] I'm studying SVMs and I'll bergin experimenting as soon as I feel a little bit more confident about what I'm doing. Just one question so far: what is the rationale for having a svm() function rather than a "svm" command?

> Dear all, > > I am just experimenting with libsvm. Overall it works fine. However, > see below an example where calling the svm() function fails. I try to > provide an alternative epsilon value for an e-SV regression from the > matrix epsval but obtain the error: > > <output> > Data types not conformable for operation > Error executing script: halting >> series yhat2 = svm(L, parms) > </output> > > <hansl> > set verbose off > open sw_ch14.gdt > series infl = 400 * log(PUNEW/PUNEW(-1)) > ntrain = 130 > test1 = ntrain + 1 > list L = infl LHUR(-1 to -3) infl(-1 to -3) > smpl L --no-missing > > # works > bundle parms = defbundle("n_train", ntrain, "quiet", 1) > parms.kernel_type=2 > parms.svm_type=3 > parms.search=1 > series yhat1 = svm(L, parms) > > # doesn't work > matrix epsval = {0.5,1} # matrix of possible eps. values > bundle parms = defbundle("n_train", ntrain, "quiet", 1) > parms.kernel_type=2 > parms.svm_type=3 > parms.search=1 > parms.epsilon=epsval[1] # error: doesnt recognize epsval[] as > scalar > series yhat2 = svm(L, parms) > </hansl> Workaround: scalar parms.epsilon=epsval[1] However, in git we'll now accept a 1x1 matrix in that sort of context.