INNER CODE UNIT · Python
transform_labels
yya518/FinBERT · archive/datasets.py:59
def transform_labels(x_y_list):
dict_labels = {'positive': 0, 'neutral':1, 'negative':2}
x_y_list_transformed = [[item[0], dict_labels[item[1]]] for item in x_y_list]
X = np.asarray([item[0] for item in x_y_list_transformed])
y = np.asarray([item[1] for item in x_y_list_transformed])
return X, y
def financialPhraseBankDataset(dir_):
fb_path = os.path.join(dir_, 'FinancialPhraseBank-v1.0')
data_50 = os.path.join(fb_path, 'Sentences_50Agree.txt')
sent_50 = []
rand_idx = 45
with open(data_50, 'rb') as fi:
for l in fi:
l = l.decode('utf-8', 'replace')
sent_50.append(l.strip())