method=SAMPLE_METHOD, vertex_group_sizes=vid2originalGroupSize_index) print('SAMPLE TIME: %.2f' % (time.time() - pt)) inv_index = groups2inv_index(groups, net.nVertices, k_set) pure_override_nodes(groups, inv_index) groups = [k_set] + groups for MAX_ITER in (300, ): pt = time.time() model = Optimizer(net, groups, dim=DIMENSION, lam=LAMBDA, eta=ETA, max_iter=MAX_ITER, epsilon=EPSILON, cg_max_iter=CG_MAX_ITER, cg_eps=CG_EPSILON, descending_method=DESCEND_METHOD, verbose=VERBOSE, sample_strategy=SAMPLE_METHOD) print('INITIAL OPTIMIZER TIME (SVD): %.2f' % (time.time() - pt)) multi_class_classification(optimizer=model, sample_filename=DATADIR + DATASET + '\\group.txt', cv=True, cross_val_fold=[2, 3, 5, 8, 10]) # multi_class_classification(optimizer=model, sample_filename=DATADIR + DATASET + '\\group.txt', cv=False) f.close()