X, y = gen_data() cnt = 250 X2, y2 = fill_data(cnt, np.min(X), np.max(X)) labels = MulticlassSOLabels(y) features = RealFeatures(X.T) model = MulticlassModel(features, labels) lambda_ = 1e1 sosvm = DualLibQPBMSOSVM(model, labels, lambda_) sosvm.set_cleanAfter(10) # number of iterations that cutting plane has to be inactive for to be removed sosvm.set_cleanICP(True) # enables inactive cutting plane removal feature sosvm.set_TolRel(0.001) # set relative tolerance sosvm.set_verbose(True) # enables verbosity of the solver sosvm.set_cp_models(16) # set number of cutting plane models sosvm.set_solver(BMRM) # select training algorithm # sosvm.set_solver(PPBMRM) # sosvm.set_solver(P3BMRM) sosvm.train() res = sosvm.get_result() Fps = np.array(res.get_hist_Fp_vector()) Fds = np.array(res.get_hist_Fp_vector()) wdists = np.array(res.get_hist_wdist_vector())
X, y = gen_data() cnt = 250 X2, y2 = fill_data(cnt, np.min(X), np.max(X)) labels = MulticlassSOLabels(y) features = RealFeatures(X.T) model = MulticlassModel(features, labels) lambda_ = 1e1 sosvm = DualLibQPBMSOSVM(model, labels, lambda_) sosvm.set_cleanAfter( 10 ) # number of iterations that cutting plane has to be inactive for to be removed sosvm.set_cleanICP(True) # enables inactive cutting plane removal feature sosvm.set_TolRel(0.001) # set relative tolerance sosvm.set_verbose(True) # enables verbosity of the solver sosvm.set_cp_models(16) # set number of cutting plane models sosvm.set_solver(BMRM) # select training algorithm #sosvm.set_solver(PPBMRM) #sosvm.set_solver(P3BMRM) sosvm.train() res = sosvm.get_result() Fps = np.array(res.get_hist_Fp_vector()) Fds = np.array(res.get_hist_Fp_vector()) wdists = np.array(res.get_hist_wdist_vector())