def test_model_by_probs(name, description, label, model):
pred_name = model.predict(name)
pred_desc = model.predict(description)
pred = pred_name + pred_desc
pred_label = vec2label(pred)
acc = accuracy_score(label, pred_label)
print(acc)
return acc
def test_dpcnn(feature, label, model):
pred = model.predict(feature)
pred_label = vec2label(pred)
acc = accuracy_score(label, pred_label)
print(acc)
return acc
def test_cic(name, feature, label, model):
pred = model.predict([name, feature])
pred_label = vec2label(pred)
acc = accuracy_score(label, pred_label)
print(acc)
return acc
def test_mul_model(name, description, label, model):
pred = model.predict([name, description])
pred_label = vec2label(pred)
acc = accuracy_score(label, pred_label)
print(acc)
return acc