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()