./afc roc in dense-train.csv csv num_folds 10 learner lr arghelp
Dense input files, dense computations, train/test experiment:
./afc roc in dense-train.csv csv testset dense-test.csv learner lr
Dense input files, sparse computations, train/test experiment:
./afc roc in dense-train.csv output rslt testset dense-test.csv learner lr
Sparse input file, sparse computations, k-fold cross-validation experiment with 10 folds:
./afc roc in spardat-train.txt:0.5+ num_folds 10 learner bc
It is possible to train on a spardat format dataset and test on a June format file:
./afc roc in spardat-train.txt:0.5+ testset june-test.inputs.ssv:june-test.outputs.ssv:rslt learner bc