def __testClassifier(self, segmentos, entities, model, fileClass):
results = []
for j in segmentos:
proc = TextCleaner(j)
procesado = proc.get_processed_comment()
vector = model.get_comment_tf_idf_vector([procesado])
supClass = load_data_from_disk(fileClass)
classifier = SC()
classifier.set_classifier(supClass)
result = classifier.classify(vector)
polaridadSup = result[0][0]
for i in entities:
if j.find(i[0]) != -1:
value = (i[0], polaridadSup)
results.append(value)
return results
def procesar(self, file, type):
if type == 1:
comentarios = []
obj = Reader(file, 1)
for i in obj.read():
for j in i:
proc = TextCleaner(j[0])
value = [proc.get_processed_comment(), j[2]]
if value[0] != "None!":
comentarios.append(value)
return comentarios
else:
obj = Reader(file, 4)
comentarios = []
for i in obj.read():
proc = TextCleaner(i[0])
value = [proc.get_processed_comment(), i[1]]
if value[0] != "None!":
comentarios.append(value)
return comentarios
