Sniffer特征

[caseware66]

def consturct_train_features(samples_train):
convert_train = []
en_labels = {
'gpt2': 0,
'gptneo': 1,
'gptj': 2,
'llama': 3,
'gpt3re': 4,
# 'gpt3sum': 4,
'human': 5
}
for item in samples_train:
label = item['label']
label_int = en_labels[label]
end_doc = item.get('end_doc', 1)

    # if label == 'human':
    #     label_int = 1
    # else:
    #     label_int = 0

    values = item['values']
    features = values['losses'] + values['lt_zero_percents'] + values[
        'std_deviations'] + values['pearson_list'] + values[
            'spearmann_list']
    if np.isnan(np.sum(features)):
        continue
    convert_train.append([features, label_int, label, end_doc])
return convert_train

您好，values['losses'] + values['lt_zero_percents'] + values[
'std_deviations'] + values['pearson_list'] + values[
'spearmann_list'] 这几个特征如何生成的？