model.fit(x=X_train,
y=y_train,
epochs=3,
batch_size=128,
verbose=2,
validation_split=0.1)
#预测
y_predict = model.predict(X_test)
#转换预测结果
y_predict_label = label2tag(predictions=y_predict, y=y)
#统计正确率
Y_test = label2tag(predictions=y_test, y=y)
print(
sum([y_predict_label[i] == Y_test[i]
for i in range(len(y_predict))]) / len(y_predict))
#导入另一个测试集进行预测，并导出结果
filename = 'xiaomi5a.csv'
test_data = pd.read_csv(filename)
x = test_data['comment']
X_cut = cut_texts(texts=x, need_cut=True, word_len=2, savepath=None)
X_seq = text2seq(texts_cut=X_cut, maxlen=maxlen, tokenizer=tokenizer)
X_seq = np.array(X_seq)
y_predict = model.predict(X_seq)
y_predict_label = label2tag(predictions=y_predict, y=y)
#Series转成dateframe
out_x = x.to_frame(name=None)
out_y = DataFrame(y_predict_label)
out_x.to_csv('x.csv')
out_y.to_csv('y.csv')
