method = HierLat(latent_factor=lafactor)
hash_file_str = str(hash(tuple(daily_data_file)))
reader = DailyWatchTimeReader()
feedback_data = reader.read_file_with_minval(daily_data_file, min_occ_user,
min_occ_prog, num_user,
num_prog)
exp_id = 'lko_bi_' + exp_name + '_data' + hash_file_str\
+ '_mu' + str(min_occ_user) + '_mp' + str(min_occ_prog) \
+ '_nu' + str(num_user) + '_np' + str(num_prog) \
+ '_k' + str(leave_k_out) + '_toiter' + str(total_iteration)
result_resource_str = 'exp' + exp_id + \
'_method' + method.unique_str() + \
'_iter' + str(iteration)
sub_folder = exp_id + '/models/' + method.unique_str()
# use a sub folder to store the experiment resource.
trained_model = URM.LoadResource(URM.RTYPE_RESULT, result_resource_str,
sub_folder)
[method] = trained_model
learnt_genre = method.V
program_mapping = feedback_data.col_mapping
program_inv_mapping = {y: x
for x, y in program_mapping.items()}
program_name = [
program_inv_mapping[i] for i in range(len(program_mapping))
leave_k_out = 20;
lafactor = 5;
method = HierLat(latent_factor=lafactor);
hash_file_str = str(hash(tuple(daily_data_file)));
reader = DailyWatchTimeReader();
feedback_data = reader.read_file_with_minval(daily_data_file, min_occ_user, min_occ_prog, num_user, num_prog);
exp_id = 'lko_bi_' + exp_name + '_data' + hash_file_str\
+ '_mu' + str(min_occ_user) + '_mp' + str(min_occ_prog) \
+ '_nu' + str(num_user) + '_np' + str(num_prog) \
+ '_k' + str(leave_k_out) + '_toiter' + str(total_iteration);
result_resource_str = 'exp' + exp_id + \
'_method' + method.unique_str() + \
'_iter' + str(iteration);
sub_folder = exp_id + '/models/' + method.unique_str(); # use a sub folder to store the experiment resource.
trained_model = URM.LoadResource(URM.RTYPE_RESULT, result_resource_str, sub_folder);
[method] = trained_model;
learnt_genre = method.V;
program_mapping = feedback_data.col_mapping;
program_inv_mapping = {y: x for x, y in program_mapping.items()};
program_name = [ program_inv_mapping[i] for i in range(len(program_mapping)) ];
sio.savemat("prog_genre_mat.mat", {'genre_mat': learnt_genre, 'prog_name': program_name});
print 'done';
