testlr2.ssc

:silent
val dir="../data/rcv1/"

val a = loadSMat(dir + "docs.smat.lz4")
val c = loadFMat(dir + "cats.fmat.lz4")
val ta = loadSMat(dir + "testdocs.smat.lz4")
val tc = loadFMat(dir + "testcats.fmat.lz4")

//val a=a0(?,0->100000);
//val c=c0(?,0->100000);

val pc = zeros(tc.nrows, tc.ncols)

class Lopts extends Learner.Options with GLM.Opts with ADAGrad.Opts with L1Regularizer.Opts with MatDS.Opts
val opts = new Lopts;

val nn = new Learner(
    new MatDS(Array(a,c), opts),
    new GLM(opts),
    null,
    null,
    opts);


opts.batchSize=1000
opts.GLM_ADAGrad =true
opts.lrate =0.1f;
opts.reg1weight = 0.01
opts.npasses=1
opts.links = iones(103,1)
opts.addConstFeat=true;

nn.train

val (mm, mopts) = GLM.predictor(nn.model, ta, pc);
mopts.addConstFeat=true;

mm.predict

val rc = roc2(pc, tc, 1-tc, 1000)
val mr = mean(rc)(0, 0->100)
val nt = sum(c,2)(0->100, 0)
val wt = nt / sum(nt);

println("ROC AUC: cat6 %5.4f, mean %5.4f" format (mr(6), (mr*wt).dv))
:silent